{# -*- coding: utf-8 -*-
from gettext import gettext as _

OLLAMA_MODELS = {
    "llama3.3": {
        "url": "https://ollama.com/library/llama3.3",
        "tags": [
                [
                        "latest",
                        "43 GB"
                ],
                [
                        "70b",
                        "43 GB"
                ]
        ],
        "author": "Meta",
        "categories": [
                "tools",
                "huge",
                "multilingual"
        ],
        "languages": [
                "en",
                "de",
                "fr",
                "it",
                "pt",
                "hi",
                "es",
                "th"
        ],
        "description": "New state of the art 70B model. Llama 3.3 70B offers similar performance compared to the Llama 3.1 405B model.",
    },
    "qwq": {
        "url": "https://ollama.com/library/qwq",
        "tags": [
                [
                        "latest",
                        "20 GB"
                ],
                [
                        "32b",
                        "20 GB"
                ]
        ],
        "author": "Qwen Team",
        "categories": [
                "tools",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "QwQ is the reasoning model of the Qwen series.",
    },
    "llama3.2-vision": {
        "url": "https://ollama.com/library/llama3.2-vision",
        "tags": [
                [
                        "latest",
                        "7.8 GB"
                ],
                [
                        "11b",
                        "7.8 GB"
                ],
                [
                        "90b",
                        "55 GB"
                ]
        ],
        "author": "Meta",
        "categories": [
                "vision",
                "medium",
                "big",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "Llama 3.2 Vision is a collection of instruction-tuned image reasoning generative models in 11B and 90B sizes.",
    },
    "llama3.2": {
        "url": "https://ollama.com/library/llama3.2",
        "tags": [
                [
                        "latest",
                        "2.0 GB"
                ],
                [
                        "1b",
                        "1.3 GB"
                ],
                [
                        "3b",
                        "2.0 GB"
                ]
        ],
        "author": "Meta",
        "categories": [
                "tools",
                "small",
                "medium",
                "big",
                "multilingual"
        ],
        "languages": [
                "en",
                "de",
                "fr",
                "it",
                "pt",
                "hi",
                "es",
                "th"
        ],
        "description": "Meta's Llama 3.2 goes small with 1B and 3B models.",
    },
    "llama3.1": {
        "url": "https://ollama.com/library/llama3.1",
        "tags": [
                [
                        "latest",
                        "4.9 GB"
                ],
                [
                        "8b",
                        "4.9 GB"
                ],
                [
                        "70b",
                        "43 GB"
                ],
                [
                        "405b",
                        "243 GB"
                ]
        ],
        "author": "Meta",
        "categories": [
                "tools",
                "small",
                "medium",
                "huge",
                "math",
                "multilingual",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "Llama 3.1 is a new state-of-the-art model from Meta available in 8B, 70B and 405B parameter sizes.",
    },
    "llama3": {
        "url": "https://ollama.com/library/llama3",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "8b",
                        "4.7 GB"
                ],
                [
                        "70b",
                        "40 GB"
                ]
        ],
        "author": "Meta",
        "categories": [
                "small",
                "medium",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "Meta Llama 3: The most capable openly available LLM to date",
    },
    "mistral": {
        "url": "https://ollama.com/library/mistral",
        "tags": [
                [
                        "latest",
                        "4.4 GB"
                ],
                [
                        "7b",
                        "4.4 GB"
                ]
        ],
        "author": "Mistral AI",
        "categories": [
                "tools",
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "The 7B model released by Mistral AI, updated to version 0.3.",
    },
    "nomic-embed-text": {
        "url": "https://ollama.com/library/nomic-embed-text",
        "tags": [
                [
                        "latest",
                        "274 MB"
                ],
                [
                        "v1.5",
                        "274 MB"
                ]
        ],
        "author": "Nomic AI",
        "categories": [
                "small",
                "medium",
                "embedding",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "A high-performing open embedding model with a large token context window.",
    },
    "gemma": {
        "url": "https://ollama.com/library/gemma",
        "tags": [
                [
                        "latest",
                        "5.0 GB"
                ],
                [
                        "2b",
                        "1.7 GB"
                ],
                [
                        "7b",
                        "5.0 GB"
                ]
        ],
        "author": "Google DeepMind",
        "categories": [
                "medium",
                "small",
                "big",
                "code",
                "math"
        ],
        "languages": [
                "en"
        ],
        "description": "Gemma is a family of lightweight, state-of-the-art open models built by Google DeepMind. Updated to version 1.1",
    },
    "qwen": {
        "url": "https://ollama.com/library/qwen",
        "tags": [
                [
                        "latest",
                        "2.3 GB"
                ],
                [
                        "0.5b",
                        "395 MB"
                ],
                [
                        "1.8b",
                        "1.1 GB"
                ],
                [
                        "4b",
                        "2.3 GB"
                ],
                [
                        "7b",
                        "4.5 GB"
                ],
                [
                        "14b",
                        "8.2 GB"
                ],
                [
                        "32b",
                        "18 GB"
                ],
                [
                        "72b",
                        "41 GB"
                ],
                [
                        "110b",
                        "63 GB"
                ]
        ],
        "author": "Alibaba",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "code",
                "math",
                "multilingual"
        ],
        "languages": [
                "en",
                "zh"
        ],
        "description": "Qwen 1.5 is a series of large language models by Alibaba Cloud spanning from 0.5B to 110B parameters",
    },
    "qwen2": {
        "url": "https://ollama.com/library/qwen2",
        "tags": [
                [
                        "latest",
                        "4.4 GB"
                ],
                [
                        "0.5b",
                        "352 MB"
                ],
                [
                        "1.5b",
                        "935 MB"
                ],
                [
                        "7b",
                        "4.4 GB"
                ],
                [
                        "72b",
                        "41 GB"
                ]
        ],
        "author": "Alibaba",
        "categories": [
                "tools",
                "small",
                "medium",
                "big",
                "huge",
                "multilingual"
        ],
        "languages": [
                "de",
                "fr",
                "es",
                "pt",
                "it",
                "nl",
                "ru",
                "cs",
                "pl",
                "ar",
                "fa",
                "he",
                "tr",
                "ja",
                "ko",
                "vi",
                "th",
                "id",
                "ms",
                "lo",
                "my",
                "ceb",
                "km",
                "tl",
                "hi",
                "bn",
                "ur"
        ],
        "description": "Qwen2 is a new series of large language models from Alibaba group",
    },
    "phi3": {
        "url": "https://ollama.com/library/phi3",
        "tags": [
                [
                        "latest",
                        "2.2 GB"
                ],
                [
                        "3.8b",
                        "2.2 GB"
                ],
                [
                        "14b",
                        "7.9 GB"
                ]
        ],
        "author": "Microsoft",
        "categories": [
                "small",
                "medium",
                "big",
                "code",
                "math"
        ],
        "languages": [
                "en"
        ],
        "description": "Phi-3 is a family of lightweight 3B (Mini) and 14B (Medium) state-of-the-art open models by Microsoft.",
    },
    "llama2": {
        "url": "https://ollama.com/library/llama2",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ],
                [
                        "70b",
                        "39 GB"
                ]
        ],
        "author": "Meta",
        "categories": [
                "small",
                "medium",
                "big",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "Llama 2 is a collection of foundation language models ranging from 7B to 70B parameters.",
    },
    "qwen2.5": {
        "url": "https://ollama.com/library/qwen2.5",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "0.5b",
                        "398 MB"
                ],
                [
                        "1.5b",
                        "986 MB"
                ],
                [
                        "3b",
                        "1.9 GB"
                ],
                [
                        "7b",
                        "4.7 GB"
                ],
                [
                        "14b",
                        "9.0 GB"
                ],
                [
                        "32b",
                        "20 GB"
                ],
                [
                        "72b",
                        "47 GB"
                ]
        ],
        "author": "Alibaba",
        "categories": [
                "tools",
                "small",
                "medium",
                "big",
                "huge",
                "multilingual"
        ],
        "languages": [
                "en",
                "zh",
                "fr",
                "es",
                "pt",
                "de",
                "it",
                "ru",
                "ja",
                "ko",
                "vi",
                "th",
                "ar"
        ],
        "description": "Qwen2.5 models are pretrained on Alibaba's latest large-scale dataset, encompassing up to 18 trillion tokens. The model supports up to 128K tokens and has multilingual support.",
    },
    "gemma2": {
        "url": "https://ollama.com/library/gemma2",
        "tags": [
                [
                        "latest",
                        "5.4 GB"
                ],
                [
                        "2b",
                        "1.6 GB"
                ],
                [
                        "9b",
                        "5.4 GB"
                ],
                [
                        "27b",
                        "16 GB"
                ]
        ],
        "author": "Google DeepMind",
        "categories": [
                "medium",
                "small",
                "big",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "Google Gemma 2 is a high-performing and efficient model available in three sizes: 2B, 9B, and 27B.",
    },
    "llava": {
        "url": "https://ollama.com/library/llava",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "7b",
                        "4.7 GB"
                ],
                [
                        "13b",
                        "8.0 GB"
                ],
                [
                        "34b",
                        "20 GB"
                ]
        ],
        "author": "Haotian Liu",
        "categories": [
                "vision",
                "small",
                "medium",
                "big",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "🌋 LLaVA is a novel end-to-end trained large multimodal model that combines a vision encoder and Vicuna for general-purpose visual and language understanding. Updated to version 1.6.",
    },
    "codellama": {
        "url": "https://ollama.com/library/codellama",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ],
                [
                        "34b",
                        "19 GB"
                ],
                [
                        "70b",
                        "39 GB"
                ]
        ],
        "author": "Meta",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "A large language model that can use text prompts to generate and discuss code.",
    },
    "qwen2.5-coder": {
        "url": "https://ollama.com/library/qwen2.5-coder",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "0.5b",
                        "398 MB"
                ],
                [
                        "1.5b",
                        "986 MB"
                ],
                [
                        "3b",
                        "1.9 GB"
                ],
                [
                        "7b",
                        "4.7 GB"
                ],
                [
                        "14b",
                        "9.0 GB"
                ],
                [
                        "32b",
                        "20 GB"
                ]
        ],
        "author": "Alibaba",
        "categories": [
                "tools",
                "small",
                "medium",
                "big",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "The latest series of Code-Specific Qwen models, with significant improvements in code generation, code reasoning, and code fixing.",
    },
    "mistral-nemo": {
        "url": "https://ollama.com/library/mistral-nemo",
        "tags": [
                [
                        "latest",
                        "7.1 GB"
                ],
                [
                        "12b",
                        "7.1 GB"
                ]
        ],
        "author": "Mistral AI",
        "categories": [
                "tools",
                "medium",
                "big",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "A state-of-the-art 12B model with 128k context length, built by Mistral AI in collaboration with NVIDIA.",
    },
    "tinyllama": {
        "url": "https://ollama.com/library/tinyllama",
        "tags": [
                [
                        "latest",
                        "638 MB"
                ],
                [
                        "1.1b",
                        "638 MB"
                ]
        ],
        "author": "TinyLlama Team",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "The TinyLlama project is an open endeavor to train a compact 1.1B Llama model on 3 trillion tokens.",
    },
    "mxbai-embed-large": {
        "url": "https://ollama.com/library/mxbai-embed-large",
        "tags": [
                [
                        "latest",
                        "670 MB"
                ],
                [
                        "335m",
                        "670 MB"
                ]
        ],
        "author": "Mixedbread.ai",
        "categories": [
                "small",
                "medium",
                "embedding"
        ],
        "languages": [
                "en"
        ],
        "description": "State-of-the-art large embedding model from mixedbread.ai",
    },
    "starcoder2": {
        "url": "https://ollama.com/library/starcoder2",
        "tags": [
                [
                        "latest",
                        "1.7 GB"
                ],
                [
                        "3b",
                        "1.7 GB"
                ],
                [
                        "7b",
                        "4.0 GB"
                ],
                [
                        "15b",
                        "9.1 GB"
                ]
        ],
        "author": "BigCode",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "StarCoder2 is the next generation of transparently trained open code LLMs that comes in three sizes: 3B, 7B and 15B parameters.",
    },
    "mixtral": {
        "url": "https://ollama.com/library/mixtral",
        "tags": [
                [
                        "latest",
                        "26 GB"
                ],
                [
                        "8x7b",
                        "26 GB"
                ],
                [
                        "8x22b",
                        "80 GB"
                ]
        ],
        "author": "Mistral AI",
        "categories": [
                "tools",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "A set of Mixture of Experts (MoE) model with open weights by Mistral AI in 8x7b and 8x22b parameter sizes.",
    },
    "dolphin-mixtral": {
        "url": "https://ollama.com/library/dolphin-mixtral",
        "tags": [
                [
                        "latest",
                        "26 GB"
                ],
                [
                        "8x7b",
                        "26 GB"
                ],
                [
                        "8x22b",
                        "80 GB"
                ]
        ],
        "author": "Eric Hartford",
        "categories": [
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "Uncensored, 8x7b and 8x22b fine-tuned models based on the Mixtral mixture of experts models that excels at coding tasks. Created by Eric Hartford.",
    },
    "codegemma": {
        "url": "https://ollama.com/library/codegemma",
        "tags": [
                [
                        "latest",
                        "5.0 GB"
                ],
                [
                        "2b",
                        "1.6 GB"
                ],
                [
                        "7b",
                        "5.0 GB"
                ]
        ],
        "author": "Google DeepMind",
        "categories": [
                "medium",
                "small",
                "big",
                "code",
                "math"
        ],
        "languages": [
                "en"
        ],
        "description": "CodeGemma is a collection of powerful, lightweight models that can perform a variety of coding tasks like fill-in-the-middle code completion, code generation, natural language understanding, mathematical reasoning, and instruction following.",
    },
    "deepseek-coder-v2": {
        "url": "https://ollama.com/library/deepseek-coder-v2",
        "tags": [
                [
                        "latest",
                        "8.9 GB"
                ],
                [
                        "16b",
                        "8.9 GB"
                ],
                [
                        "236b",
                        "133 GB"
                ]
        ],
        "author": "DeepSeek Team",
        "categories": [
                "medium",
                "big",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "An open-source Mixture-of-Experts code language model that achieves performance comparable to GPT4-Turbo in code-specific tasks.",
    },
    "phi": {
        "url": "https://ollama.com/library/phi",
        "tags": [
                [
                        "latest",
                        "1.6 GB"
                ],
                [
                        "2.7b",
                        "1.6 GB"
                ]
        ],
        "author": "Microsoft",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "Phi-2: a 2.7B language model by Microsoft Research that demonstrates outstanding reasoning and language understanding capabilities.",
    },
    "llama2-uncensored": {
        "url": "https://ollama.com/library/llama2-uncensored",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ],
                [
                        "70b",
                        "39 GB"
                ]
        ],
        "author": "George Sung, Jarrad Hope",
        "categories": [
                "small",
                "medium",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "Uncensored Llama 2 model by George Sung and Jarrad Hope.",
    },
    "deepseek-coder": {
        "url": "https://ollama.com/library/deepseek-coder",
        "tags": [
                [
                        "latest",
                        "776 MB"
                ],
                [
                        "1.3b",
                        "776 MB"
                ],
                [
                        "6.7b",
                        "3.8 GB"
                ],
                [
                        "33b",
                        "19 GB"
                ]
        ],
        "author": "DeepSeek Team",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "code",
                "multilingual"
        ],
        "languages": [
                "en",
                "zh"
        ],
        "description": "DeepSeek Coder is a capable coding model trained on two trillion code and natural language tokens.",
    },
    "snowflake-arctic-embed": {
        "url": "https://ollama.com/library/snowflake-arctic-embed",
        "tags": [
                [
                        "latest",
                        "669 MB"
                ],
                [
                        "22m",
                        "46 MB"
                ],
                [
                        "33m",
                        "67 MB"
                ],
                [
                        "110m",
                        "219 MB"
                ],
                [
                        "137m",
                        "274 MB"
                ],
                [
                        "335m",
                        "669 MB"
                ]
        ],
        "author": "Snowflake",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "embedding"
        ],
        "languages": [
                "en"
        ],
        "description": "A suite of text embedding models by Snowflake, optimized for performance.",
    },
    "wizardlm2": {
        "url": "https://ollama.com/library/wizardlm2",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ],
                [
                        "8x22b",
                        "80 GB"
                ]
        ],
        "author": "Microsoft",
        "categories": [
                "small",
                "medium",
                "huge",
                "multilingual"
        ],
        "languages": [
                "en"
        ],
        "description": "State of the art large language model from Microsoft AI with improved performance on complex chat, multilingual, reasoning and agent use cases.",
    },
    "dolphin-mistral": {
        "url": "https://ollama.com/library/dolphin-mistral",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ]
        ],
        "author": "Eric Hartford",
        "categories": [
                "small",
                "medium",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "The uncensored Dolphin model based on Mistral that excels at coding tasks. Updated to version 2.8.",
    },
    "dolphin-llama3": {
        "url": "https://ollama.com/library/dolphin-llama3",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "8b",
                        "4.7 GB"
                ],
                [
                        "70b",
                        "40 GB"
                ]
        ],
        "author": "Eric Hartford",
        "categories": [
                "small",
                "medium",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "Dolphin 2.9 is a new model with 8B and 70B sizes by Eric Hartford based on Llama 3 that has a variety of instruction, conversational, and coding skills.",
    },
    "yi": {
        "url": "https://ollama.com/library/yi",
        "tags": [
                [
                        "latest",
                        "3.5 GB"
                ],
                [
                        "6b",
                        "3.5 GB"
                ],
                [
                        "9b",
                        "5.0 GB"
                ],
                [
                        "34b",
                        "19 GB"
                ]
        ],
        "author": "01.AI",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "multilingual"
        ],
        "languages": [
                "en",
                "zh"
        ],
        "description": "Yi 1.5 is a high-performing, bilingual language model.",
    },
    "command-r": {
        "url": "https://ollama.com/library/command-r",
        "tags": [
                [
                        "latest",
                        "19 GB"
                ],
                [
                        "35b",
                        "19 GB"
                ]
        ],
        "author": "Cohere",
        "categories": [
                "tools",
                "big",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "Command R is a Large Language Model optimized for conversational interaction and long context tasks.",
    },
    "orca-mini": {
        "url": "https://ollama.com/library/orca-mini",
        "tags": [
                [
                        "latest",
                        "2.0 GB"
                ],
                [
                        "3b",
                        "2.0 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ],
                [
                        "70b",
                        "39 GB"
                ]
        ],
        "author": "Orca Mini Team",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "math"
        ],
        "languages": [
                "en"
        ],
        "description": "A general-purpose model ranging from 3 billion parameters to 70 billion, suitable for entry-level hardware.",
    },
    "llava-llama3": {
        "url": "https://ollama.com/library/llava-llama3",
        "tags": [
                [
                        "latest",
                        "5.5 GB"
                ],
                [
                        "8b",
                        "5.5 GB"
                ]
        ],
        "author": "Xtuner",
        "categories": [
                "vision",
                "medium",
                "big"
        ],
        "languages": [
                "en"
        ],
        "description": "A LLaVA model fine-tuned from Llama 3 Instruct with better scores in several benchmarks.",
    },
    "zephyr": {
        "url": "https://ollama.com/library/zephyr",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ],
                [
                        "141b",
                        "80 GB"
                ]
        ],
        "author": "Hugging Face H4",
        "categories": [
                "small",
                "medium",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "Zephyr is a series of fine-tuned versions of the Mistral and Mixtral models that are trained to act as helpful assistants.",
    },
    "phi3.5": {
        "url": "https://ollama.com/library/phi3.5",
        "tags": [
                [
                        "latest",
                        "2.2 GB"
                ],
                [
                        "3.8b",
                        "2.2 GB"
                ]
        ],
        "author": "Microsoft",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "A lightweight AI model with 3.8 billion parameters with performance overtaking similarly and larger sized models.",
    },
    "all-minilm": {
        "url": "https://ollama.com/library/all-minilm",
        "tags": [
                [
                        "latest",
                        "46 MB"
                ],
                [
                        "22m",
                        "46 MB"
                ],
                [
                        "33m",
                        "67 MB"
                ]
        ],
        "author": "Sentence Transformers",
        "categories": [
                "small",
                "medium",
                "big",
                "embedding"
        ],
        "languages": [
                "en"
        ],
        "description": "Embedding models on very large sentence level datasets.",
    },
    "codestral": {
        "url": "https://ollama.com/library/codestral",
        "tags": [
                [
                        "latest",
                        "13 GB"
                ],
                [
                        "22b",
                        "13 GB"
                ]
        ],
        "author": "Mistral AI",
        "categories": [
                "big",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "Codestral is Mistral AI’s first-ever code model designed for code generation tasks.",
    },
    "starcoder": {
        "url": "https://ollama.com/library/starcoder",
        "tags": [
                [
                        "latest",
                        "1.8 GB"
                ],
                [
                        "1b",
                        "726 MB"
                ],
                [
                        "3b",
                        "1.8 GB"
                ],
                [
                        "7b",
                        "4.3 GB"
                ],
                [
                        "15b",
                        "9.0 GB"
                ]
        ],
        "author": "BigCode",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "StarCoder is a code generation model trained on 80+ programming languages.",
    },
    "vicuna": {
        "url": "https://ollama.com/library/vicuna",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ],
                [
                        "33b",
                        "18 GB"
                ]
        ],
        "author": "lmsys.org",
        "categories": [
                "small",
                "medium",
                "big",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "General use chat model based on Llama and Llama 2 with 2K to 16K context sizes.",
    },
    "granite-code": {
        "url": "https://ollama.com/library/granite-code",
        "tags": [
                [
                        "latest",
                        "2.0 GB"
                ],
                [
                        "3b",
                        "2.0 GB"
                ],
                [
                        "8b",
                        "4.6 GB"
                ],
                [
                        "20b",
                        "12 GB"
                ],
                [
                        "34b",
                        "19 GB"
                ]
        ],
        "author": "IBM for Code Intelligence",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "A family of open foundation models by IBM for Code Intelligence",
    },
    "mistral-openorca": {
        "url": "https://ollama.com/library/mistral-openorca",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ]
        ],
        "author": "Open Orca",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "Mistral OpenOrca is a 7 billion parameter model, fine-tuned on top of the Mistral 7B model using the OpenOrca dataset.",
    },
    "smollm": {
        "url": "https://ollama.com/library/smollm",
        "tags": [
                [
                        "latest",
                        "991 MB"
                ],
                [
                        "135m",
                        "92 MB"
                ],
                [
                        "360m",
                        "229 MB"
                ],
                [
                        "1.7b",
                        "991 MB"
                ]
        ],
        "author": "Hugging Face TB",
        "categories": [
                "small",
                "medium",
                "big",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "🪐 A family of small models with 135M, 360M, and 1.7B parameters, trained on a new high-quality dataset.",
    },
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        "url": "https://ollama.com/library/wizard-vicuna-uncensored",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ],
                [
                        "30b",
                        "18 GB"
                ]
        ],
        "author": "Eric Hartford",
        "categories": [
                "small",
                "medium",
                "big",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "Wizard Vicuna Uncensored is a 7B, 13B, and 30B parameter model based on Llama 2 uncensored by Eric Hartford.",
    },
    "llama2-chinese": {
        "url": "https://ollama.com/library/llama2-chinese",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ]
        ],
        "author": "Meta",
        "categories": [
                "small",
                "medium",
                "big",
                "multilingual"
        ],
        "languages": [
                "en",
                "zh"
        ],
        "description": "Llama 2 based model fine tuned to improve Chinese dialogue ability.",
    },
    "bge-m3": {
        "url": "https://ollama.com/library/bge-m3",
        "tags": [
                [
                        "latest",
                        "1.2 GB"
                ],
                [
                        "567m",
                        "1.2 GB"
                ]
        ],
        "author": "BGE-m3 Team",
        "categories": [
                "small",
                "medium",
                "embedding"
        ],
        "languages": [
                "en"
        ],
        "description": "BGE-M3 is a new model from BAAI distinguished for its versatility in Multi-Functionality, Multi-Linguality, and Multi-Granularity.",
    },
    "codegeex4": {
        "url": "https://ollama.com/library/codegeex4",
        "tags": [
                [
                        "latest",
                        "5.5 GB"
                ],
                [
                        "9b",
                        "5.5 GB"
                ]
        ],
        "author": "THUDM",
        "categories": [
                "medium",
                "big",
                "code",
                "multilingual"
        ],
        "languages": [
                "en",
                "zh"
        ],
        "description": "A versatile model for AI software development scenarios, including code completion.",
    },
    "openchat": {
        "url": "https://ollama.com/library/openchat",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ]
        ],
        "author": "OpenChat Team",
        "categories": [
                "small",
                "medium",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "A family of open-source models trained on a wide variety of data, surpassing ChatGPT on various benchmarks. Updated to version 3.5-0106.",
    },
    "aya": {
        "url": "https://ollama.com/library/aya",
        "tags": [
                [
                        "latest",
                        "4.8 GB"
                ],
                [
                        "8b",
                        "4.8 GB"
                ],
                [
                        "35b",
                        "20 GB"
                ]
        ],
        "author": "Cohere",
        "categories": [
                "small",
                "medium",
                "huge",
                "multilingual"
        ],
        "languages": [
                "en"
        ],
        "description": "Aya 23, released by Cohere, is a new family of state-of-the-art, multilingual models that support 23 languages.",
    },
    "codeqwen": {
        "url": "https://ollama.com/library/codeqwen",
        "tags": [
                [
                        "latest",
                        "4.2 GB"
                ],
                [
                        "7b",
                        "4.2 GB"
                ]
        ],
        "author": "Alibaba",
        "categories": [
                "small",
                "medium",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "CodeQwen1.5 is a large language model pretrained on a large amount of code data.",
    },
    "nous-hermes2": {
        "url": "https://ollama.com/library/nous-hermes2",
        "tags": [
                [
                        "latest",
                        "6.1 GB"
                ],
                [
                        "10.7b",
                        "6.1 GB"
                ],
                [
                        "34b",
                        "19 GB"
                ]
        ],
        "author": "Nous Research",
        "categories": [
                "medium",
                "big",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "The powerful family of models by Nous Research that excels at scientific discussion and coding tasks.",
    },
    "command-r-plus": {
        "url": "https://ollama.com/library/command-r-plus",
        "tags": [
                [
                        "latest",
                        "59 GB"
                ],
                [
                        "104b",
                        "59 GB"
                ]
        ],
        "author": "Cohere",
        "categories": [
                "tools",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "Command R+ is a powerful, scalable large language model purpose-built to excel at real-world enterprise use cases.",
    },
    "wizardcoder": {
        "url": "https://ollama.com/library/wizardcoder",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "33b",
                        "19 GB"
                ]
        ],
        "author": "WizardLM Team",
        "categories": [
                "small",
                "big",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "State-of-the-art code generation model",
    },
    "stable-code": {
        "url": "https://ollama.com/library/stable-code",
        "tags": [
                [
                        "latest",
                        "1.6 GB"
                ],
                [
                        "3b",
                        "1.6 GB"
                ]
        ],
        "author": "Stability AI",
        "categories": [
                "small",
                "medium",
                "code",
                "math"
        ],
        "languages": [
                "en"
        ],
        "description": "Stable Code 3B is a coding model with instruct and code completion variants on par with models such as Code Llama 7B that are 2.5x larger.",
    },
    "tinydolphin": {
        "url": "https://ollama.com/library/tinydolphin",
        "tags": [
                [
                        "latest",
                        "637 MB"
                ],
                [
                        "1.1b",
                        "637 MB"
                ]
        ],
        "author": "Eric Hartford",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "An experimental 1.1B parameter model trained on the new Dolphin 2.8 dataset by Eric Hartford and based on TinyLlama.",
    },
    "openhermes": {
        "url": "https://ollama.com/library/openhermes",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "v2",
                        "4.1 GB"
                ],
                [
                        "v2.5",
                        "4.1 GB"
                ]
        ],
        "author": "Teknium",
        "categories": [
                "small",
                "medium",
                "big"
        ],
        "languages": [
                "en"
        ],
        "description": "OpenHermes 2.5 is a 7B model fine-tuned by Teknium on Mistral with fully open datasets.",
    },
    "mistral-large": {
        "url": "https://ollama.com/library/mistral-large",
        "tags": [
                [
                        "latest",
                        "73 GB"
                ],
                [
                        "123b",
                        "73 GB"
                ]
        ],
        "author": "Mistral AI",
        "categories": [
                "tools",
                "huge",
                "code",
                "math"
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        "languages": [
                "en"
        ],
        "description": "Mistral Large 2 is Mistral's new flagship model that is significantly more capable in code generation, mathematics, and reasoning with 128k context window and support for dozens of languages.",
    },
    "qwen2-math": {
        "url": "https://ollama.com/library/qwen2-math",
        "tags": [
                [
                        "latest",
                        "4.4 GB"
                ],
                [
                        "1.5b",
                        "935 MB"
                ],
                [
                        "7b",
                        "4.4 GB"
                ],
                [
                        "72b",
                        "41 GB"
                ]
        ],
        "author": "Alibaba",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "math"
        ],
        "languages": [
                "en"
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        "description": "Qwen2 Math is a series of specialized math language models built upon the Qwen2 LLMs, which significantly outperforms the mathematical capabilities of open-source models and even closed-source models (e.g., GPT4o).",
    },
    "glm4": {
        "url": "https://ollama.com/library/glm4",
        "tags": [
                [
                        "latest",
                        "5.5 GB"
                ],
                [
                        "9b",
                        "5.5 GB"
                ]
        ],
        "author": "THUDM",
        "categories": [
                "medium",
                "big",
                "code",
                "math"
        ],
        "languages": [
                "en"
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        "description": "A strong multi-lingual general language model with competitive performance to Llama 3.",
    },
    "stablelm2": {
        "url": "https://ollama.com/library/stablelm2",
        "tags": [
                [
                        "latest",
                        "983 MB"
                ],
                [
                        "1.6b",
                        "983 MB"
                ],
                [
                        "12b",
                        "7.0 GB"
                ]
        ],
        "author": "Stability AI",
        "categories": [
                "small",
                "medium",
                "big",
                "multilingual"
        ],
        "languages": [
                "en",
                "es",
                "de",
                "it",
                "fr",
                "pt",
                "nl"
        ],
        "description": "Stable LM 2 is a state-of-the-art 1.6B and 12B parameter language model trained on multilingual data in English, Spanish, German, Italian, French, Portuguese, and Dutch.",
    },
    "bakllava": {
        "url": "https://ollama.com/library/bakllava",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "7b",
                        "4.7 GB"
                ]
        ],
        "author": "Skunkworks AI",
        "categories": [
                "vision",
                "small",
                "medium"
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        "languages": [
                "en"
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        "description": "BakLLaVA is a multimodal model consisting of the Mistral 7B base model augmented with the LLaVA architecture.",
    },
    "reflection": {
        "url": "https://ollama.com/library/reflection",
        "tags": [
                [
                        "latest",
                        "40 GB"
                ],
                [
                        "70b",
                        "40 GB"
                ]
        ],
        "author": "Matt Shumer",
        "categories": [
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "A high-performing model trained with a new technique called Reflection-tuning that teaches a LLM to detect mistakes in its reasoning and correct course.",
    },
    "deepseek-llm": {
        "url": "https://ollama.com/library/deepseek-llm",
        "tags": [
                [
                        "latest",
                        "4.0 GB"
                ],
                [
                        "7b",
                        "4.0 GB"
                ],
                [
                        "67b",
                        "38 GB"
                ]
        ],
        "author": "DeepSeek Team",
        "categories": [
                "small",
                "medium",
                "huge",
                "multilingual",
                "code",
                "math"
        ],
        "languages": [
                "en",
                "zh"
        ],
        "description": "An advanced language model crafted with 2 trillion bilingual tokens.",
    },
    "llama3-gradient": {
        "url": "https://ollama.com/library/llama3-gradient",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "8b",
                        "4.7 GB"
                ],
                [
                        "70b",
                        "40 GB"
                ]
        ],
        "author": "Gradient AI",
        "categories": [
                "small",
                "medium",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "This model extends LLama-3 8B's context length from 8k to over 1m tokens.",
    },
    "wizard-math": {
        "url": "https://ollama.com/library/wizard-math",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ],
                [
                        "70b",
                        "39 GB"
                ]
        ],
        "author": "WizardLM Team",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "math"
        ],
        "languages": [
                "en"
        ],
        "description": "Model focused on math and logic problems",
    },
    "moondream": {
        "url": "https://ollama.com/library/moondream",
        "tags": [
                [
                        "latest",
                        "1.7 GB"
                ],
                [
                        "1.8b",
                        "1.7 GB"
                ]
        ],
        "author": "Vikhyatk",
        "categories": [
                "vision",
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "moondream2 is a small vision language model designed to run efficiently on edge devices.",
    },
    "neural-chat": {
        "url": "https://ollama.com/library/neural-chat",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ]
        ],
        "author": "Intel",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "A fine-tuned model based on Mistral with good coverage of domain and language.",
    },
    "llama3-chatqa": {
        "url": "https://ollama.com/library/llama3-chatqa",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "8b",
                        "4.7 GB"
                ],
                [
                        "70b",
                        "40 GB"
                ]
        ],
        "author": "Nvidia",
        "categories": [
                "small",
                "medium",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "A model from NVIDIA based on Llama 3 that excels at conversational question answering (QA) and retrieval-augmented generation (RAG).",
    },
    "xwinlm": {
        "url": "https://ollama.com/library/xwinlm",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ]
        ],
        "author": "Xwin LM",
        "categories": [
                "small",
                "medium",
                "big"
        ],
        "languages": [
                "en"
        ],
        "description": "Conversational model based on Llama 2 that performs competitively on various benchmarks.",
    },
    "sqlcoder": {
        "url": "https://ollama.com/library/sqlcoder",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ],
                [
                        "15b",
                        "9.0 GB"
                ]
        ],
        "author": "Defog.ai",
        "categories": [
                "small",
                "medium",
                "big",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "SQLCoder is a code completion model fined-tuned on StarCoder for SQL generation tasks",
    },
    "nous-hermes": {
        "url": "https://ollama.com/library/nous-hermes",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ]
        ],
        "author": "Nous Research",
        "categories": [
                "small",
                "medium",
                "big"
        ],
        "languages": [
                "en"
        ],
        "description": "General use models based on Llama and Llama 2 from Nous Research.",
    },
    "phind-codellama": {
        "url": "https://ollama.com/library/phind-codellama",
        "tags": [
                [
                        "latest",
                        "19 GB"
                ],
                [
                        "34b",
                        "19 GB"
                ]
        ],
        "author": "Phind",
        "categories": [
                "big",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "Code generation model based on Code Llama.",
    },
    "yarn-llama2": {
        "url": "https://ollama.com/library/yarn-llama2",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ]
        ],
        "author": "Nous Research",
        "categories": [
                "small",
                "medium",
                "big"
        ],
        "languages": [
                "en"
        ],
        "description": "An extension of Llama 2 that supports a context of up to 128k tokens.",
    },
    "dolphincoder": {
        "url": "https://ollama.com/library/dolphincoder",
        "tags": [
                [
                        "latest",
                        "4.2 GB"
                ],
                [
                        "7b",
                        "4.2 GB"
                ],
                [
                        "15b",
                        "9.1 GB"
                ]
        ],
        "author": "Cognitive Computations",
        "categories": [
                "small",
                "medium",
                "big",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "A 7B and 15B uncensored variant of the Dolphin model family that excels at coding, based on StarCoder2.",
    },
    "wizardlm": {
        "url": "https://ollama.com/library/wizardlm",
        "tags": [
                [
                        "7b-q2_K",
                        "2.8 GB"
                ],
                [
                        "7b-q3_K_S",
                        "2.9 GB"
                ],
                [
                        "7b-q3_K_M",
                        "3.3 GB"
                ]
        ],
        "author": "WizardLM Team",
        "categories": [
                "small",
                "medium",
                "big"
        ],
        "languages": [
                "en"
        ],
        "description": "General use model based on Llama 2.",
    },
    "deepseek-v2": {
        "url": "https://ollama.com/library/deepseek-v2",
        "tags": [
                [
                        "latest",
                        "8.9 GB"
                ],
                [
                        "16b",
                        "8.9 GB"
                ],
                [
                        "236b",
                        "133 GB"
                ]
        ],
        "author": "DeepSeek Team",
        "categories": [
                "medium",
                "big",
                "huge",
                "multilingual"
        ],
        "languages": [
                "en",
                "zh"
        ],
        "description": "A strong, economical, and efficient Mixture-of-Experts language model.",
    },
    "starling-lm": {
        "url": "https://ollama.com/library/starling-lm",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ]
        ],
        "author": "Berkeley Nest",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "Starling is a large language model trained by reinforcement learning from AI feedback focused on improving chatbot helpfulness.",
    },
    "samantha-mistral": {
        "url": "https://ollama.com/library/samantha-mistral",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ]
        ],
        "author": "Eric Hartford",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "A companion assistant trained in philosophy, psychology, and personal relationships. Based on Mistral.",
    },
    "hermes3": {
        "url": "https://ollama.com/library/hermes3",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "3b",
                        "2.0 GB"
                ],
                [
                        "8b",
                        "4.7 GB"
                ],
                [
                        "70b",
                        "40 GB"
                ],
                [
                        "405b",
                        "229 GB"
                ]
        ],
        "author": "Nous Research ",
        "categories": [
                "tools",
                "small",
                "medium",
                "big",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "Hermes 3 is the latest version of the flagship Hermes series of LLMs by Nous Research",
    },
    "yi-coder": {
        "url": "https://ollama.com/library/yi-coder",
        "tags": [
                [
                        "latest",
                        "5.0 GB"
                ],
                [
                        "1.5b",
                        "866 MB"
                ],
                [
                        "9b",
                        "5.0 GB"
                ]
        ],
        "author": "01.AI",
        "categories": [
                "medium",
                "small",
                "big",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "Yi-Coder is a series of open-source code language models that delivers state-of-the-art coding performance with fewer than 10 billion parameters.",
    },
    "falcon": {
        "url": "https://ollama.com/library/falcon",
        "tags": [
                [
                        "latest",
                        "4.2 GB"
                ],
                [
                        "7b",
                        "4.2 GB"
                ],
                [
                        "40b",
                        "24 GB"
                ],
                [
                        "180b",
                        "101 GB"
                ]
        ],
        "author": "Technology Innovation Institute",
        "categories": [
                "small",
                "medium",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "A large language model built by the Technology Innovation Institute (TII) for use in summarization, text generation, and chat bots.",
    },
    "internlm2": {
        "url": "https://ollama.com/library/internlm2",
        "tags": [
                [
                        "latest",
                        "4.5 GB"
                ],
                [
                        "1m",
                        "4.5 GB"
                ],
                [
                        "1.8b",
                        "1.1 GB"
                ],
                [
                        "7b",
                        "4.5 GB"
                ],
                [
                        "20b",
                        "11 GB"
                ]
        ],
        "author": "Intern LM",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "math"
        ],
        "languages": [
                "en"
        ],
        "description": "InternLM2.5 is a 7B parameter model tailored for practical scenarios with outstanding reasoning capability.",
    },
    "solar": {
        "url": "https://ollama.com/library/solar",
        "tags": [
                [
                        "latest",
                        "6.1 GB"
                ],
                [
                        "10.7b",
                        "6.1 GB"
                ]
        ],
        "author": "Upstage",
        "categories": [
                "medium",
                "big"
        ],
        "languages": [
                "en"
        ],
        "description": "A compact, yet powerful 10.7B large language model designed for single-turn conversation.",
    },
    "athene-v2": {
        "url": "https://ollama.com/library/athene-v2",
        "tags": [
                [
                        "latest",
                        "47 GB"
                ],
                [
                        "72b",
                        "47 GB"
                ]
        ],
        "author": "Nexusflow",
        "categories": [
                "tools",
                "huge",
                "code",
                "math"
        ],
        "languages": [
                "en"
        ],
        "description": "Athene-V2 is a 72B parameter model which excels at code completion, mathematics, and log extraction tasks.",
    },
    "llava-phi3": {
        "url": "https://ollama.com/library/llava-phi3",
        "tags": [
                [
                        "latest",
                        "2.9 GB"
                ],
                [
                        "3.8b",
                        "2.9 GB"
                ]
        ],
        "author": "Xtuner",
        "categories": [
                "vision",
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "A new small LLaVA model fine-tuned from Phi 3 Mini.",
    },
    "orca2": {
        "url": "https://ollama.com/library/orca2",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ]
        ],
        "author": "Microsoft Research",
        "categories": [
                "small",
                "medium",
                "big",
                "math"
        ],
        "languages": [
                "en"
        ],
        "description": "Orca 2 is built by Microsoft research, and are a fine-tuned version of Meta's Llama 2 models. The model is designed to excel particularly in reasoning.",
    },
    "minicpm-v": {
        "url": "https://ollama.com/library/minicpm-v",
        "tags": [
                [
                        "latest",
                        "5.5 GB"
                ],
                [
                        "8b",
                        "5.5 GB"
                ]
        ],
        "author": "OpenBMB",
        "categories": [
                "vision",
                "medium",
                "big",
                "math",
                "multilingual",
                "code"
        ],
        "languages": [
                "en",
                "zh",
                "de",
                "fr",
                "it",
                "ko"
        ],
        "description": "A series of multimodal LLMs (MLLMs) designed for vision-language understanding.",
    },
    "stable-beluga": {
        "url": "https://ollama.com/library/stable-beluga",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ],
                [
                        "70b",
                        "39 GB"
                ]
        ],
        "author": "Stability AI",
        "categories": [
                "small",
                "medium",
                "big",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "Llama 2 based model fine tuned on an Orca-style dataset. Originally called Free Willy.",
    },
    "mistral-small": {
        "url": "https://ollama.com/library/mistral-small",
        "tags": [
                [
                        "latest",
                        "14 GB"
                ],
                [
                        "22b",
                        "13 GB"
                ],
                [
                        "24b",
                        "14 GB"
                ]
        ],
        "author": "Mistral AI",
        "categories": [
                "tools",
                "big",
                "huge",
                "code",
                "math"
        ],
        "languages": [
                "en"
        ],
        "description": "Mistral Small 3 sets a new benchmark in the “small” Large Language Models category below 70B.",
    },
    "dolphin-phi": {
        "url": "https://ollama.com/library/dolphin-phi",
        "tags": [
                [
                        "latest",
                        "1.6 GB"
                ],
                [
                        "2.7b",
                        "1.6 GB"
                ]
        ],
        "author": "Eric Hartford",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "2.7B uncensored Dolphin model by Eric Hartford, based on the Phi language model by Microsoft Research.",
    },
    "smollm2": {
        "url": "https://ollama.com/library/smollm2",
        "tags": [
                [
                        "latest",
                        "1.8 GB"
                ],
                [
                        "135m",
                        "271 MB"
                ],
                [
                        "360m",
                        "726 MB"
                ],
                [
                        "1.7b",
                        "1.8 GB"
                ]
        ],
        "author": "Hugging Face TB",
        "categories": [
                "tools",
                "small",
                "medium",
                "big",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "SmolLM2 is a family of compact language models available in three size: 135M, 360M, and 1.7B parameters.",
    },
    "wizardlm-uncensored": {
        "url": "https://ollama.com/library/wizardlm-uncensored",
        "tags": [
                [
                        "latest",
                        "7.4 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ]
        ],
        "author": "TheBloke AI",
        "categories": [
                "medium",
                "big"
        ],
        "languages": [
                "en"
        ],
        "description": "Uncensored version of Wizard LM model",
    },
    "nemotron-mini": {
        "url": "https://ollama.com/library/nemotron-mini",
        "tags": [
                [
                        "latest",
                        "2.7 GB"
                ],
                [
                        "4b",
                        "2.7 GB"
                ]
        ],
        "author": "Nvidia",
        "categories": [
                "tools",
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "A commercial-friendly small language model by NVIDIA optimized for roleplay, RAG QA, and function calling.",
    },
    "yarn-mistral": {
        "url": "https://ollama.com/library/yarn-mistral",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ]
        ],
        "author": "Nous Research",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "An extension of Mistral to support context windows of 64K or 128K.",
    },
    "llama-pro": {
        "url": "https://ollama.com/library/llama-pro",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "instruct",
                        "4.7 GB"
                ],
                [
                        "text",
                        "4.7 GB"
                ]
        ],
        "author": "Tencent",
        "categories": [
                "small",
                "medium",
                "big",
                "math"
        ],
        "languages": [
                "en"
        ],
        "description": "An expansion of Llama 2 that specializes in integrating both general language understanding and domain-specific knowledge, particularly in programming and mathematics.",
    },
    "medllama2": {
        "url": "https://ollama.com/library/medllama2",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ]
        ],
        "author": "Siraj Raval",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "Fine-tuned Llama 2 model to answer medical questions based on an open source medical dataset.",
    },
    "meditron": {
        "url": "https://ollama.com/library/meditron",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ],
                [
                        "70b",
                        "39 GB"
                ]
        ],
        "author": "EPFL LLM Team",
        "categories": [
                "small",
                "medium",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "Open-source medical large language model adapted from Llama 2 to the medical domain.",
    },
    "llama3-groq-tool-use": {
        "url": "https://ollama.com/library/llama3-groq-tool-use",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "8b",
                        "4.7 GB"
                ],
                [
                        "70b",
                        "40 GB"
                ]
        ],
        "author": "Groq",
        "categories": [
                "tools",
                "small",
                "medium",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "A series of models from Groq that represent a significant advancement in open-source AI capabilities for tool use/function calling.",
    },
    "nemotron": {
        "url": "https://ollama.com/library/nemotron",
        "tags": [
                [
                        "latest",
                        "43 GB"
                ],
                [
                        "70b",
                        "43 GB"
                ]
        ],
        "author": "Nvidia",
        "categories": [
                "tools",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "Llama-3.1-Nemotron-70B-Instruct is a large language model customized by NVIDIA to improve the helpfulness of LLM generated responses to user queries.",
    },
    "nexusraven": {
        "url": "https://ollama.com/library/nexusraven",
        "tags": [
                [
                        "latest",
                        "7.4 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ]
        ],
        "author": "NexusFlow AI",
        "categories": [
                "medium",
                "big"
        ],
        "languages": [
                "en"
        ],
        "description": "Nexus Raven is a 13B instruction tuned model for function calling tasks.",
    },
    "nous-hermes2-mixtral": {
        "url": "https://ollama.com/library/nous-hermes2-mixtral",
        "tags": [
                [
                        "latest",
                        "26 GB"
                ],
                [
                        "8x7b",
                        "26 GB"
                ]
        ],
        "author": "Nous Research",
        "categories": [
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "The Nous Hermes 2 model from Nous Research, now trained over Mixtral.",
    },
    "codeup": {
        "url": "https://ollama.com/library/codeup",
        "tags": [
                [
                        "latest",
                        "7.4 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ]
        ],
        "author": "DeepSE",
        "categories": [
                "medium",
                "big",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "Great code generation model based on Llama2.",
    },
    "everythinglm": {
        "url": "https://ollama.com/library/everythinglm",
        "tags": [
                [
                        "latest",
                        "7.4 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ]
        ],
        "author": "Totally Not An LLM",
        "categories": [
                "medium",
                "big"
        ],
        "languages": [
                "en"
        ],
        "description": "Uncensored Llama2 based model with support for a 16K context window.",
    },
    "granite3-dense": {
        "url": "https://ollama.com/library/granite3-dense",
        "tags": [
                [
                        "latest",
                        "1.6 GB"
                ],
                [
                        "2b",
                        "1.6 GB"
                ],
                [
                        "8b",
                        "4.9 GB"
                ]
        ],
        "author": "IBM Research",
        "categories": [
                "tools",
                "small",
                "medium",
                "big",
                "code",
                "multilingual"
        ],
        "languages": [
                "en",
                "de",
                "es",
                "fr",
                "ja",
                "pt",
                "ar",
                "cs",
                "it",
                "ko",
                "nl",
                "zh"
        ],
        "description": "The IBM Granite 2B and 8B models are designed to support tool-based use cases and support for retrieval augmented generation (RAG), streamlining code generation, translation and bug fixing.",
    },
    "magicoder": {
        "url": "https://ollama.com/library/magicoder",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ]
        ],
        "author": "iSE",
        "categories": [
                "small",
                "medium",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "🎩 Magicoder is a family of 7B parameter models trained on 75K synthetic instruction data using OSS-Instruct, a novel approach to enlightening LLMs with open-source code snippets.",
    },
    "stablelm-zephyr": {
        "url": "https://ollama.com/library/stablelm-zephyr",
        "tags": [
                [
                        "latest",
                        "1.6 GB"
                ],
                [
                        "3b",
                        "1.6 GB"
                ]
        ],
        "author": "Stability AI",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "A lightweight chat model allowing accurate, and responsive output without requiring high-end hardware.",
    },
    "codebooga": {
        "url": "https://ollama.com/library/codebooga",
        "tags": [
                [
                        "latest",
                        "19 GB"
                ],
                [
                        "34b",
                        "19 GB"
                ]
        ],
        "author": "Oobabooga",
        "categories": [
                "big",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "A high-performing code instruct model created by merging two existing code models.",
    },
    "falcon2": {
        "url": "https://ollama.com/library/falcon2",
        "tags": [
                [
                        "latest",
                        "6.4 GB"
                ],
                [
                        "11b",
                        "6.4 GB"
                ]
        ],
        "author": "Technology Innovation Institute",
        "categories": [
                "medium",
                "big",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "Falcon2 is an 11B parameters causal decoder-only model built by TII and trained over 5T tokens.",
    },
    "wizard-vicuna": {
        "url": "https://ollama.com/library/wizard-vicuna",
        "tags": [
                [
                        "latest",
                        "7.4 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ]
        ],
        "author": "MelodysDreamj",
        "categories": [
                "medium",
                "big"
        ],
        "languages": [
                "en"
        ],
        "description": "Wizard Vicuna is a 13B parameter model based on Llama 2 trained by MelodysDreamj.",
    },
    "mistrallite": {
        "url": "https://ollama.com/library/mistrallite",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ]
        ],
        "author": "Amazon Web Services",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "MistralLite is a fine-tuned model based on Mistral with enhanced capabilities of processing long contexts.",
    },
    "mathstral": {
        "url": "https://ollama.com/library/mathstral",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ]
        ],
        "author": "Mistral AI",
        "categories": [
                "small",
                "medium",
                "math"
        ],
        "languages": [
                "en"
        ],
        "description": "MathΣtral: a 7B model designed for math reasoning and scientific discovery by Mistral AI.",
    },
    "duckdb-nsql": {
        "url": "https://ollama.com/library/duckdb-nsql",
        "tags": [
                [
                        "latest",
                        "3.8 GB"
                ],
                [
                        "7b",
                        "3.8 GB"
                ]
        ],
        "author": "MotherDuck, Numbers Station",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "7B parameter text-to-SQL model made by MotherDuck and Numbers Station.",
    },
    "megadolphin": {
        "url": "https://ollama.com/library/megadolphin",
        "tags": [
                [
                        "latest",
                        "68 GB"
                ],
                [
                        "120b",
                        "68 GB"
                ]
        ],
        "author": "Cognitive Computations",
        "categories": [
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "MegaDolphin-2.2-120b is a transformation of Dolphin-2.2-70b created by interleaving the model with itself.",
    },
    "solar-pro": {
        "url": "https://ollama.com/library/solar-pro",
        "tags": [
                [
                        "latest",
                        "13 GB"
                ],
                [
                        "22b",
                        "13 GB"
                ]
        ],
        "author": "Upstage",
        "categories": [
                "big",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "Solar Pro Preview: an advanced large language model (LLM) with 22 billion parameters designed to fit into a single GPU",
    },
    "reader-lm": {
        "url": "https://ollama.com/library/reader-lm",
        "tags": [
                [
                        "latest",
                        "935 MB"
                ],
                [
                        "0.5b",
                        "352 MB"
                ],
                [
                        "1.5b",
                        "935 MB"
                ]
        ],
        "author": "JinaAI",
        "categories": [
                "small",
                "medium",
                "big"
        ],
        "languages": [
                "en"
        ],
        "description": "A series of models that convert HTML content to Markdown content, which is useful for content conversion tasks.",
    },
    "notux": {
        "url": "https://ollama.com/library/notux",
        "tags": [
                [
                        "latest",
                        "26 GB"
                ],
                [
                        "8x7b",
                        "26 GB"
                ]
        ],
        "author": "Argilla",
        "categories": [
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "A top-performing mixture of experts model, fine-tuned with high-quality data.",
    },
    "notus": {
        "url": "https://ollama.com/library/notus",
        "tags": [
                [
                        "latest",
                        "4.1 GB"
                ],
                [
                        "7b",
                        "4.1 GB"
                ]
        ],
        "author": "Argilla",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "A 7B chat model fine-tuned with high-quality data and based on Zephyr.",
    },
    "open-orca-platypus2": {
        "url": "https://ollama.com/library/open-orca-platypus2",
        "tags": [
                [
                        "latest",
                        "7.4 GB"
                ],
                [
                        "13b",
                        "7.4 GB"
                ]
        ],
        "author": "Open Orca",
        "categories": [
                "medium",
                "big",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "Merge of the Open Orca OpenChat model and the Garage-bAInd Platypus 2 model. Designed for chat and code generation.",
    },
    "goliath": {
        "url": "https://ollama.com/library/goliath",
        "tags": [
                [
                        "latest",
                        "66 GB"
                ]
        ],
        "author": "Alpindale",
        "categories": [
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "A language model created by combining two fine-tuned Llama 2 70B models into one.",
    },
    "granite3-moe": {
        "url": "https://ollama.com/library/granite3-moe",
        "tags": [
                [
                        "latest",
                        "822 MB"
                ],
                [
                        "1b",
                        "822 MB"
                ],
                [
                        "3b",
                        "2.1 GB"
                ]
        ],
        "author": "IBM Research",
        "categories": [
                "tools",
                "small",
                "medium",
                "big",
                "multilingual",
                "code"
        ],
        "languages": [
                "en",
                "de",
                "es",
                "fr",
                "ja",
                "pt",
                "ar",
                "cs",
                "it",
                "ko",
                "nl",
                "zh"
        ],
        "description": "The IBM Granite 1B and 3B models are the first mixture of experts (MoE) Granite models from IBM designed for low latency usage.",
    },
    "nuextract": {
        "url": "https://ollama.com/library/nuextract",
        "tags": [
                [
                        "latest",
                        "2.2 GB"
                ],
                [
                        "3.8b",
                        "2.2 GB"
                ]
        ],
        "author": "Numind",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "A 3.8B model fine-tuned on a private high-quality synthetic dataset for information extraction, based on Phi-3.",
    },
    "aya-expanse": {
        "url": "https://ollama.com/library/aya-expanse",
        "tags": [
                [
                        "latest",
                        "5.1 GB"
                ],
                [
                        "8b",
                        "5.1 GB"
                ],
                [
                        "32b",
                        "20 GB"
                ]
        ],
        "author": "Cohere For AI",
        "categories": [
                "tools",
                "medium",
                "big",
                "huge",
                "multilingual"
        ],
        "languages": [
                "en",
                "ar",
                "zh",
                "cs",
                "nl",
                "fr",
                "de",
                "el",
                "he",
                "hi",
                "id",
                "it",
                "ja",
                "ko",
                "fa",
                "pl",
                "pt",
                "ro",
                "ru",
                "es",
                "tr",
                "uk",
                "vi"
        ],
        "description": "Cohere For AI's language models trained to perform well across 23 different languages.",
    },
    "dbrx": {
        "url": "https://ollama.com/library/dbrx",
        "tags": [
                [
                        "latest",
                        "74 GB"
                ],
                [
                        "132b",
                        "74 GB"
                ]
        ],
        "author": "Databricks",
        "categories": [
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "DBRX is an open, general-purpose LLM created by Databricks.",
    },
    "marco-o1": {
        "url": "https://ollama.com/library/marco-o1",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "7b",
                        "4.7 GB"
                ]
        ],
        "author": "AIDC-AI",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "An open large reasoning model for real-world solutions by the Alibaba International Digital Commerce Group (AIDC-AI).",
    },
    "bge-large": {
        "url": "https://ollama.com/library/bge-large",
        "tags": [
                [
                        "latest",
                        "671 MB"
                ],
                [
                        "335m",
                        "671 MB"
                ]
        ],
        "author": "BGE Large Team",
        "categories": [
                "small",
                "medium",
                "embedding"
        ],
        "languages": [
                "en"
        ],
        "description": "Embedding model from BAAI mapping texts to vectors.",
    },
    "firefunction-v2": {
        "url": "https://ollama.com/library/firefunction-v2",
        "tags": [
                [
                        "latest",
                        "40 GB"
                ],
                [
                        "70b",
                        "40 GB"
                ]
        ],
        "author": "Fireworks AI",
        "categories": [
                "tools",
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "An open weights function calling model based on Llama 3, competitive with GPT-4o function calling capabilities.",
    },
    "alfred": {
        "url": "https://ollama.com/library/alfred",
        "tags": [
                [
                        "latest",
                        "24 GB"
                ],
                [
                        "40b",
                        "24 GB"
                ]
        ],
        "author": "LightOn AI",
        "categories": [
                "huge"
        ],
        "languages": [
                "en"
        ],
        "description": "A robust conversational model designed to be used for both chat and instruct use cases.",
    },
    "deepseek-v2.5": {
        "url": "https://ollama.com/library/deepseek-v2.5",
        "tags": [
                [
                        "latest",
                        "133 GB"
                ],
                [
                        "236b",
                        "133 GB"
                ]
        ],
        "author": "DeepSeek Team",
        "categories": [
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "An upgraded version of DeekSeek-V2 that integrates the general and coding abilities of both DeepSeek-V2-Chat and DeepSeek-Coder-V2-Instruct.",
    },
    "shieldgemma": {
        "url": "https://ollama.com/library/shieldgemma",
        "tags": [
                [
                        "latest",
                        "5.8 GB"
                ],
                [
                        "2b",
                        "1.7 GB"
                ],
                [
                        "9b",
                        "5.8 GB"
                ],
                [
                        "27b",
                        "17 GB"
                ]
        ],
        "author": "Google DeepMind",
        "categories": [
                "medium",
                "small",
                "big",
                "huge",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "ShieldGemma is set of instruction tuned models for evaluating the safety of text prompt input and text output responses against a set of defined safety policies.",
    },
    "bespoke-minicheck": {
        "url": "https://ollama.com/library/bespoke-minicheck",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "7b",
                        "4.7 GB"
                ]
        ],
        "author": "Bespoke Labs",
        "categories": [
                "small",
                "medium"
        ],
        "languages": [
                "en"
        ],
        "description": "A state-of-the-art fact-checking model developed by Bespoke Labs.",
    },
    "llama-guard3": {
        "url": "https://ollama.com/library/llama-guard3",
        "tags": [
                [
                        "latest",
                        "4.9 GB"
                ],
                [
                        "1b",
                        "1.6 GB"
                ],
                [
                        "8b",
                        "4.9 GB"
                ]
        ],
        "author": "Meta",
        "categories": [
                "small",
                "medium",
                "big",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "Llama Guard 3 is a series of models fine-tuned for content safety classification of LLM inputs and responses.",
    },
    "paraphrase-multilingual": {
        "url": "https://ollama.com/library/paraphrase-multilingual",
        "tags": [
                [
                        "latest",
                        "563 MB"
                ],
                [
                        "278m",
                        "563 MB"
                ]
        ],
        "author": "Paraphrase Team",
        "categories": [
                "small",
                "medium",
                "multilingual",
                "embedding"
        ],
        "languages": [
                "en"
        ],
        "description": "Sentence-transformers model that can be used for tasks like clustering or semantic search.",
    },
    "opencoder": {
        "url": "https://ollama.com/library/opencoder",
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "1.5b",
                        "1.4 GB"
                ],
                [
                        "8b",
                        "4.7 GB"
                ]
        ],
        "author": "Infly AI",
        "categories": [
                "small",
                "medium",
                "big",
                "code",
                "multilingual"
        ],
        "languages": [
                "en",
                "zh"
        ],
        "description": "OpenCoder is an open and reproducible code LLM family which includes 1.5B and 8B models, supporting chat in English and Chinese languages.",
    },
    "tulu3": {
        "url": "https://ollama.com/library/tulu3",
        "tags": [
                [
                        "latest",
                        "4.9 GB"
                ],
                [
                        "8b",
                        "4.9 GB"
                ],
                [
                        "70b",
                        "43 GB"
                ]
        ],
        "author": "The Allen Institute for AI",
        "categories": [
                "small",
                "medium",
                "huge",
                "code",
                "math"
        ],
        "languages": [
                "en"
        ],
        "description": "Tülu 3 is a leading instruction following model family, offering fully open-source data, code, and recipes by the The Allen Institute for AI.",
    },
    "snowflake-arctic-embed2": {
        "url": "https://ollama.com/library/snowflake-arctic-embed2",
        "tags": [
                [
                        "latest",
                        "1.2 GB"
                ],
                [
                        "568m",
                        "1.2 GB"
                ]
        ],
        "author": "Snowflake Team",
        "categories": [
                "small",
                "medium",
                "embedding",
                "multilingual"
        ],
        "languages": [
                "en",
                "fr",
                "es",
                "it",
                "de"
        ],
        "description": "Snowflake's frontier embedding model. Arctic Embed 2.0 adds multilingual support without sacrificing English performance or scalability.",
    },
    "granite3-guardian": {
        "url": "https://ollama.com/library/granite3-guardian",
        "tags": [
                [
                        "latest",
                        "2.7 GB"
                ],
                [
                        "2b",
                        "2.7 GB"
                ],
                [
                        "8b",
                        "5.8 GB"
                ]
        ],
        "author": "IBM Research",
        "categories": [
                "small",
                "medium",
                "big",
                "code"
        ],
        "languages": [
                "en"
        ],
        "description": "The IBM Granite Guardian 3.0 2B and 8B models are designed to detect risks in prompts and/or responses.",
    },
    "exaone3.5": {
        "url": "https://ollama.com/library/exaone3.5",
        "tags": [
                [
                        "latest",
                        "4.8 GB"
                ],
                [
                        "2.4b",
                        "1.6 GB"
                ],
                [
                        "7.8b",
                        "4.8 GB"
                ],
                [
                        "32b",
                        "19 GB"
                ]
        ],
        "author": "LG AI Research",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "multilingual"
        ],
        "languages": [
                "en",
                "ko"
        ],
        "description": "EXAONE 3.5 is a collection of instruction-tuned bilingual (English and Korean) generative models ranging from 2.4B to 32B parameters, developed and released by LG AI Research.",
    },
    "sailor2": {
        "url": "https://ollama.com/library/sailor2",
        "tags": [
                [
                        "latest",
                        "5.2 GB"
                ],
                [
                        "1b",
                        "1.1 GB"
                ],
                [
                        "8b",
                        "5.2 GB"
                ],
                [
                        "20b",
                        "12 GB"
                ]
        ],
        "author": "Sailor2 Community",
        "categories": [
                "medium",
                "small",
                "big",
                "huge",
                "multilingual",
                "code"
        ],
        "languages": [
                "en",
                "zh",
                "my",
                "ceb",
                "ilo",
                "id",
                "jv",
                "km",
                "lo",
                "ms",
                "su",
                "tl",
                "th",
                "vi",
                "war"
        ],
        "description": "Sailor2 are multilingual language models made for South-East Asia. Available in 1B, 8B, and 20B parameter sizes.",
    },
    "falcon3": {
        "tags": [
                [
                        "latest",
                        "4.6 GB"
                ],
                [
                        "1b",
                        "1.8 GB"
                ],
                [
                        "3b",
                        "2.0 GB"
                ],
                [
                        "7b",
                        "4.6 GB"
                ],
                [
                        "10b",
                        "6.3 GB"
                ]
        ],
        "url": "https://ollama.com/library/falcon3",
        "categories": [
                "small",
                "medium",
                "big",
                "huge",
                "code",
                "math"
        ],
        "author": "Technology Innovation Institute",
        "languages": [
                "en"
        ],
        "description": "A family of efficient AI models under 10B parameters performant in science, math, and coding through innovative training techniques.",
    },
    "granite3.1-dense": {
        "tags": [
                [
                        "latest",
                        "5.0 GB"
                ],
                [
                        "2b",
                        "1.6 GB"
                ],
                [
                        "8b",
                        "5.0 GB"
                ]
        ],
        "url": "https://ollama.com/library/granite3.1-dense",
        "categories": [
                "tools",
                "medium",
                "small",
                "big",
                "code",
                "multilingual"
        ],
        "author": "IBM Research",
        "languages": [
                "en",
                "de",
                "es",
                "fr",
                "ja",
                "pt",
                "ar",
                "cs",
                "it",
                "ko",
                "nl",
                "zh"
        ],
        "description": "The IBM Granite 2B and 8B models are text-only dense LLMs trained on over 12 trillion tokens of data, demonstrated significant improvements over their predecessors in performance and speed in IBM’s initial testing.",
    },
    "granite3.1-moe": {
        "tags": [
                [
                        "latest",
                        "2.0 GB"
                ],
                [
                        "1b",
                        "1.4 GB"
                ],
                [
                        "3b",
                        "2.0 GB"
                ]
        ],
        "url": "https://ollama.com/library/granite3.1-moe",
        "categories": [
                "tools",
                "small",
                "medium",
                "big",
                "multilingual",
                "code"
        ],
        "author": "IBM Research",
        "languages": [
                "en",
                "de",
                "es",
                "fr",
                "ja",
                "pt",
                "ar",
                "cs",
                "it",
                "ko",
                "nl",
                "zh"
        ],
        "description": "The IBM Granite 1B and 3B models are long-context mixture of experts (MoE) Granite models from IBM designed for low latency usage.",
    },
    "granite-embedding": {
        "tags": [
                [
                        "latest",
                        "63 MB"
                ],
                [
                        "30m",
                        "63 MB"
                ],
                [
                        "278m",
                        "563 MB"
                ]
        ],
        "url": "https://ollama.com/library/granite-embedding",
        "categories": [
                "small",
                "medium",
                "big",
                "embedding",
                "code",
                "multilingual"
        ],
        "author": "IBM Research",
        "languages": [
                "en",
                "de",
                "es",
                "fr",
                "ja",
                "pt",
                "ar",
                "cs",
                "it",
                "ko",
                "nl",
                "zh"
        ],
        "description": "The IBM Granite Embedding 30M and 278M models models are text-only dense biencoder embedding models, with 30M available in English only and 278M serving multilingual use cases.",
    },
    "phi4": {
        "tags": [
                [
                        "latest",
                        "9.1 GB"
                ],
                [
                        "14b",
                        "9.1 GB"
                ]
        ],
        "url": "https://ollama.com/library/phi4",
        "categories": [
                "medium",
                "big"
        ],
        "author": "Microsoft",
        "languages": [
                "en"
        ],
        "description": "Phi-4 is a 14B parameter, state-of-the-art open model from Microsoft.",
    },
    "smallthinker": {
        "tags": [
                [
                        "latest",
                        "3.6 GB"
                ],
                [
                        "3b",
                        "3.6 GB"
                ]
        ],
        "url": "https://ollama.com/library/smallthinker",
        "categories": [
                "small",
                "medium"
        ],
        "author": "Power Infer",
        "languages": [
                "en"
        ],
        "description": "A new small reasoning model fine-tuned from the Qwen 2.5 3B Instruct model.",
    },
    "dolphin3": {
        "tags": [
                [
                        "latest",
                        "4.9 GB"
                ],
                [
                        "8b",
                        "4.9 GB"
                ]
        ],
        "url": "https://ollama.com/library/dolphin3",
        "categories": [
                "small",
                "medium",
                "code",
                "math"
        ],
        "author": "Cognitive Computations",
        "languages": [
                "en"
        ],
        "description": "Dolphin 3.0 Llama 3.1 8B 🐬 is the next generation of the Dolphin series of instruct-tuned models designed to be the ultimate general purpose local model, enabling coding, math, agentic, function calling, and general use cases.",
    },
    "deepseek-r1": {
        "tags": [
                [
                        "latest",
                        "5.2 GB"
                ],
                [
                        "1.5b",
                        "1.1 GB"
                ],
                [
                        "7b",
                        "4.7 GB"
                ],
                [
                        "8b",
                        "5.2 GB"
                ],
                [
                        "14b",
                        "9.0 GB"
                ],
                [
                        "32b",
                        "20 GB"
                ],
                [
                        "70b",
                        "43 GB"
                ],
                [
                        "671b",
                        "404 GB"
                ]
        ],
        "url": "https://ollama.com/library/deepseek-r1",
        "categories": [
                "tools",
                "medium",
                "small",
                "big",
                "huge",
                "math"
        ],
        "author": "DeepSeek Team",
        "languages": [
                "en"
        ],
        "description": "DeepSeek-R1 is a family of open reasoning models with performance approaching that of leading models, such as O3 and Gemini 2.5 Pro.",
    },
    "deepseek-v3": {
        "tags": [
                [
                        "latest",
                        "404 GB"
                ],
                [
                        "671b",
                        "404 GB"
                ]
        ],
        "url": "https://ollama.com/library/deepseek-v3",
        "categories": [
                "huge"
        ],
        "author": "DeepSeek Team",
        "languages": [
                "en"
        ],
        "description": "A strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token.",
    },
    "olmo2": {
        "tags": [
                [
                        "latest",
                        "4.5 GB"
                ],
                [
                        "7b",
                        "4.5 GB"
                ],
                [
                        "13b",
                        "8.4 GB"
                ]
        ],
        "url": "https://ollama.com/library/olmo2",
        "categories": [
                "small",
                "medium",
                "big"
        ],
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                "en"
        ],
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    },
    "command-r7b": {
        "tags": [
                [
                        "latest",
                        "5.1 GB"
                ],
                [
                        "7b",
                        "5.1 GB"
                ]
        ],
        "url": "https://ollama.com/library/command-r7b",
        "categories": [
                "tools",
                "medium",
                "big",
                "code",
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                "fr",
                "es",
                "it",
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                "pt",
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                "cs",
                "id",
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                "hi",
                "he",
                "fa"
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        "description": "The smallest model in Cohere's R series delivers top-tier speed, efficiency, and quality to build powerful AI applications on commodity GPUs and edge devices.",
    },
    "openthinker": {
        "tags": [
                [
                        "latest",
                        "4.7 GB"
                ],
                [
                        "7b",
                        "4.7 GB"
                ],
                [
                        "32b",
                        "20 GB"
                ]
        ],
        "url": "https://ollama.com/library/openthinker",
        "categories": [
                "small",
                "medium",
                "huge"
        ],
        "author": "Open Thoughts Team",
        "languages": [
                "en"
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    },
    "deepscaler": {
        "tags": [
                [
                        "latest",
                        "3.6 GB"
                ],
                [
                        "1.5b",
                        "3.6 GB"
                ]
        ],
        "url": "https://ollama.com/library/deepscaler",
        "categories": [
                "small",
                "medium",
                "math"
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        "author": "Agentica Project",
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                "en"
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    },
    "r1-1776": {
        "tags": [
                [
                        "latest",
                        "43 GB"
                ],
                [
                        "70b",
                        "43 GB"
                ],
                [
                        "671b",
                        "404 GB"
                ]
        ],
        "url": "https://ollama.com/library/r1-1776",
        "categories": [
                "huge",
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                "math"
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                "zh",
                "ja"
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    },
    "gemma3": {
        "tags": [
                [
                        "latest",
                        "3.3 GB"
                ],
                [
                        "270m",
                        "292 MB"
                ],
                [
                        "1b",
                        "815 MB"
                ],
                [
                        "4b",
                        "3.3 GB"
                ],
                [
                        "12b",
                        "8.1 GB"
                ],
                [
                        "27b",
                        "17 GB"
                ]
        ],
        "url": "https://ollama.com/library/gemma3",
        "categories": [
                "vision",
                "small",
                "medium",
                "big",
                "huge"
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                "en"
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        "description": "The current, most capable model that runs on a single GPU.",
    },
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        "tags": [
                [
                        "latest",
                        "2.5 GB"
                ],
                [
                        "3.8b",
                        "2.5 GB"
                ]
        ],
        "url": "https://ollama.com/library/phi4-mini",
        "categories": [
                "tools",
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                "medium",
                "math",
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                "zh",
                "cs",
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                "nl",
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                "no",
                "pl",
                "pt",
                "ru",
                "es",
                "sv",
                "th",
                "tr",
                "uk"
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        "description": "Phi-4-mini brings significant enhancements in multilingual support, reasoning, and mathematics, and now, the long-awaited function calling feature is finally supported.",
    },
    "granite3.2-vision": {
        "tags": [
                [
                        "latest",
                        "2.4 GB"
                ],
                [
                        "2b",
                        "2.4 GB"
                ]
        ],
        "url": "https://ollama.com/library/granite3.2-vision",
        "categories": [
                "vision",
                "tools",
                "small",
                "medium"
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        "languages": [
                "en"
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    },
    "granite3.2": {
        "tags": [
                [
                        "latest",
                        "4.9 GB"
                ],
                [
                        "2b",
                        "1.5 GB"
                ],
                [
                        "8b",
                        "4.9 GB"
                ]
        ],
        "url": "https://ollama.com/library/granite3.2",
        "categories": [
                "tools",
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                "medium",
                "big",
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                "es",
                "fr",
                "ja",
                "pt",
                "ar",
                "cs",
                "it",
                "ko",
                "nl",
                "zh"
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        "description": "Granite-3.2 is a family of long-context AI models from IBM Granite fine-tuned for thinking capabilities.",
    },
    "command-r7b-arabic": {
        "tags": [
                [
                        "latest",
                        "5.1 GB"
                ],
                [
                        "7b",
                        "5.1 GB"
                ]
        ],
        "url": "https://ollama.com/library/command-r7b-arabic",
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                "big"
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                "ar"
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    },
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        "tags": [
                [
                        "latest",
                        "67 GB"
                ],
                [
                        "111b",
                        "67 GB"
                ]
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        "url": "https://ollama.com/library/command-a",
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                "code"
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                "id",
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                "ro",
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    },
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        "tags": [
                [
                        "latest",
                        "5.2 GB"
                ],
                [
                        "0.6b",
                        "523 MB"
                ],
                [
                        "1.7b",
                        "1.4 GB"
                ],
                [
                        "4b",
                        "2.5 GB"
                ],
                [
                        "8b",
                        "5.2 GB"
                ],
                [
                        "14b",
                        "9.3 GB"
                ],
                [
                        "30b",
                        "19 GB"
                ],
                [
                        "32b",
                        "20 GB"
                ],
                [
                        "235b",
                        "142 GB"
                ]
        ],
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                        "14 GB"
                ],
                [
                        "24b",
                        "14 GB"
                ]
        ],
        "description": "Devstral: the best open source model for coding agents",
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                "big",
                "huge",
                "code"
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                "en"
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        "tags": [
                [
                        "latest",
                        "67 GB"
                ],
                [
                        "16x17b",
                        "67 GB"
                ],
                [
                        "128x17b",
                        "245 GB"
                ]
        ],
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                "code"
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                "vi"
        ],
    },
    "qwen2.5vl": {
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                [
                        "latest",
                        "6.0 GB"
                ],
                [
                        "3b",
                        "3.2 GB"
                ],
                [
                        "7b",
                        "6.0 GB"
                ],
                [
                        "32b",
                        "21 GB"
                ],
                [
                        "72b",
                        "49 GB"
                ]
        ],
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                "medium",
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                "huge",
                "math"
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                "en"
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                        "latest",
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                        "1.5b",
                        "1.1 GB"
                ],
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                        "14b",
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        ],
        "description": "DeepCoder is a fully open-Source 14B coder model at O3-mini level, with a 1.5B version also available.",
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                "small",
                "big",
                "code"
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                "en"
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                        "latest",
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                ]
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                "en"
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                        "latest",
                        "4.9 GB"
                ],
                [
                        "3b",
                        "2.2 GB"
                ],
                [
                        "8b",
                        "4.9 GB"
                ],
                [
                        "14b",
                        "9.0 GB"
                ],
                [
                        "32b",
                        "20 GB"
                ],
                [
                        "70b",
                        "43 GB"
                ]
        ],
        "description": "Cogito v1 Preview is a family of hybrid reasoning models by Deep Cogito that outperform the best available open models of the same size, including counterparts from LLaMA, DeepSeek, and Qwen across most standard benchmarks.",
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                "en"
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                        "latest",
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                ],
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                        "2b",
                        "1.5 GB"
                ],
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                        "8b",
                        "4.9 GB"
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                        "latest",
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                        "14b",
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                "en"
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                        "latest",
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                ],
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                        "2.4b",
                        "1.6 GB"
                ],
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                        "7.8b",
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                ],
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                        "19 GB"
                ]
        ],
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                "huge",
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                "en"
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                        "3.8b",
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                "math"
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                "en"
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                        "latest",
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                ],
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                        "e2b",
                        "5.6 GB"
                ],
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                        "e4b",
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        "description": "Gemma 3n models are designed for efficient execution on everyday devices such as laptops, tablets or phones.",
        "url": "https://ollama.com/library/gemma3n",
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                "huge"
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                "en"
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                        "latest",
                        "14 GB"
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                        "20b",
                        "14 GB"
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                [
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                        "65 GB"
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        "description": "OpenAI’s open-weight models designed for powerful reasoning, agentic tasks, and versatile developer use cases.",
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                "big",
                "huge"
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                "en"
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                        "latest",
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                [
                        "30b",
                        "19 GB"
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                [
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                        "290 GB"
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                "huge",
                "code"
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                "en"
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                "medium",
                "embedding",
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                ]
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                "huge"
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}