From f44200bec80f777e7b15c118202ba8a33143a05c Mon Sep 17 00:00:00 2001 From: rampa3 <68955305+rampa3@users.noreply.github.com> Date: Mon, 9 Feb 2026 09:10:37 +0100 Subject: [PATCH] chore(model gallery): Add Ministral 3 family of models (aside from base versions) (#8467) Signed-off-by: rampa3 <68955305+rampa3@users.noreply.github.com> --- gallery/index.yaml | 305 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 305 insertions(+) diff --git a/gallery/index.yaml b/gallery/index.yaml index 5987dcdb1..06fce3c0c 100644 --- a/gallery/index.yaml +++ b/gallery/index.yaml @@ -12398,6 +12398,311 @@ - filename: llama-cpp/mmproj/mmproj-mistral-community_pixtral-12b-f16.gguf sha256: a0b21e5a3b0f9b0b604385c45bb841142e7a5ac7660fa6a397dbc87c66b2083e uri: huggingface://bartowski/mistral-community_pixtral-12b-GGUF/mmproj-mistral-community_pixtral-12b-f16.gguf +- !!merge <<: *mistral03 + name: "mistralai_ministral-3-14b-instruct-2512-multimodal" + urls: + - https://huggingface.co/mistralai/Ministral-3-14B-Instruct-2512 + - https://huggingface.co/unsloth/Ministral-3-14B-Instruct-2512-GGUF + description: | + The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. A powerful and efficient language model with vision capabilities. + + The Ministral 3 family is designed for edge deployment, capable of running on a wide range of hardware. Ministral 3 14B can even be deployed locally, capable of fitting in 24GB of VRAM in FP8, and less if further quantized. + + Key Features: + Ministral 3 14B consists of two main architectural components: + + - 13.5B Language Model + - 0.4B Vision Encoder + + The Ministral 3 14B Instruct model offers the following capabilities: + + - Vision: Enables the model to analyze images and provide insights based on visual content, in addition to text. + - Multilingual: Supports dozens of languages, including English, French, Spanish, German, Italian, Portuguese, Dutch, Chinese, Japanese, Korean, Arabic. + - System Prompt: Maintains strong adherence and support for system prompts. + - Agentic: Offers best-in-class agentic capabilities with native function calling and JSON outputting. + - Edge-Optimized: Delivers best-in-class performance at a small scale, deployable anywhere. + - Apache 2.0 License: Open-source license allowing usage and modification for both commercial and non-commercial purposes. + - Large Context Window: Supports a 256k context window. + + This gallery entry includes mmproj for multimodality and uses Unsloth recommended defaults. + tags: + - llm + - gguf + - gpu + - mistral + - cpu + - function-calling + - multimodal + overrides: + context_size: 16384 + parameters: + model: llama-cpp/models/mistralai_Ministral-3-14B-Instruct-2512-Q4_K_M.gguf + temperature: 0.15 + mmproj: llama-cpp/mmproj/mmproj-mistralai_Ministral-3-14B-Instruct-2512-f32.gguf + files: + - filename: llama-cpp/models/mistralai_Ministral-3-14B-Instruct-2512-Q4_K_M.gguf + sha256: 76ce697c065f2e40f1e8e958118b02cab38e2c10a6015f7d7908036a292dc8c8 + uri: huggingface://unsloth/Ministral-3-14B-Instruct-2512-GGUF/Ministral-3-14B-Instruct-2512-Q4_K_M.gguf + - filename: llama-cpp/mmproj/mmproj-mistralai_Ministral-3-14B-Instruct-2512-f32.gguf + sha256: 2740ba9e9b30b09be4282a9a9f617ec43dc47b89aed416cb09b5f698f90783b5 + uri: huggingface://unsloth/Ministral-3-14B-Instruct-2512-GGUF/mmproj-F32.gguf +- !!merge <<: *mistral03 + name: "mistralai_ministral-3-14b-reasoning-2512-multimodal" + urls: + - https://huggingface.co/mistralai/Ministral-3-14B-Reasoning-2512 + - https://huggingface.co/unsloth/Ministral-3-14B-Reasoning-2512-GGUF + description: | + The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. A powerful and efficient language model with vision capabilities. + + This model is the reasoning post-trained version, trained for reasoning tasks, making it ideal for math, coding and stem related use cases. + + The Ministral 3 family is designed for edge deployment, capable of running on a wide range of hardware. Ministral 3 14B can even be deployed locally, capable of fitting in 32GB of VRAM in BF16, and less than 24GB of RAM/VRAM when quantized. + + Key Features: + Ministral 3 14B consists of two main architectural components: + + + - 13.5B Language Model + - 0.4B Vision Encoder + + The Ministral 3 14B Reasoning model offers the following capabilities: + + + - Vision: Enables the model to analyze images and provide insights based on visual content, in addition to text. + - Multilingual: Supports dozens of languages, including English, French, Spanish, German, Italian, Portuguese, Dutch, Chinese, Japanese, Korean, Arabic. + - System Prompt: Maintains strong adherence and support for system prompts. + - Agentic: Offers best-in-class agentic capabilities with native function calling and JSON outputting. + - Reasoning: Excels at complex, multi-step reasoning and dynamic problem-solving. + - Edge-Optimized: Delivers best-in-class performance at a small scale, deployable anywhere. + - Apache 2.0 License: Open-source license allowing usage and modification for both commercial and non-commercial purposes. + - Large Context Window: Supports a 256k context window. + + + This gallery entry includes mmproj for multimodality and uses Unsloth recommended defaults. + tags: + - llm + - gguf + - gpu + - mistral + - cpu + - function-calling + - multimodal + overrides: + context_size: 32768 + parameters: + model: llama-cpp/models/mistralai_Ministral-3-14B-Reasoning-2512-Q4_K_M.gguf + temperature: 0.7 + top_p: 0.95 + mmproj: llama-cpp/mmproj/mmproj-mistralai_Ministral-3-14B-Reasoning-2512-f32.gguf + files: + - filename: llama-cpp/models/mistralai_Ministral-3-14B-Reasoning-2512-Q4_K_M.gguf + sha256: f577390559b89ebdbfe52cc234ea334649c24e6003ffa4b6a2474c5e2a47aa17 + uri: huggingface://unsloth/Ministral-3-14B-Reasoning-2512-GGUF/Ministral-3-14B-Reasoning-2512-Q4_K_M.gguf + - filename: llama-cpp/mmproj/mmproj-mistralai_Ministral-3-14B-Reasoning-2512-f32.gguf + sha256: 891bf262a032968f6e5b3d4e9ffc84cf6381890033c2f5204fbdf4817af4ab9b + uri: huggingface://unsloth/Ministral-3-14B-Reasoning-2512-GGUF/mmproj-F32.gguf +- !!merge <<: *mistral03 + name: "mistralai_ministral-3-8b-instruct-2512-multimodal" + urls: + - https://huggingface.co/mistralai/Ministral-3-8B-Instruct-2512 + - https://huggingface.co/unsloth/Ministral-3-8B-Instruct-2512-GGUF + description: | + A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities. + + The Ministral 3 family is designed for edge deployment, capable of running on a wide range of hardware. Ministral 3 8B can even be deployed locally, capable of fitting in 12GB of VRAM in FP8, and less if further quantized. + + Key Features: + Ministral 3 8B consists of two main architectural components: + + - 8.4B Language Model + - 0.4B Vision Encoder + + The Ministral 3 8B Instruct model offers the following capabilities: + + - Vision: Enables the model to analyze images and provide insights based on visual content, in addition to text. + - Multilingual: Supports dozens of languages, including English, French, Spanish, German, Italian, Portuguese, Dutch, Chinese, Japanese, Korean, Arabic. + - System Prompt: Maintains strong adherence and support for system prompts. + - Agentic: Offers best-in-class agentic capabilities with native function calling and JSON outputting. + - Edge-Optimized: Delivers best-in-class performance at a small scale, deployable anywhere. + - Apache 2.0 License: Open-source license allowing usage and modification for both commercial and non-commercial purposes. + - Large Context Window: Supports a 256k context window. + + This gallery entry includes mmproj for multimodality and uses Unsloth recommended defaults. + tags: + - llm + - gguf + - gpu + - mistral + - cpu + - function-calling + - multimodal + overrides: + context_size: 16384 + parameters: + model: llama-cpp/models/mistralai_Ministral-3-8B-Instruct-2512-Q4_K_M.gguf + temperature: 0.15 + mmproj: llama-cpp/mmproj/mmproj-mistralai_Ministral-3-8B-Instruct-2512-f32.gguf + files: + - filename: llama-cpp/models/mistralai_Ministral-3-8B-Instruct-2512-Q4_K_M.gguf + sha256: 5dbc3647eb563b9f8d3c70ec3d906cce84b86bb35c5e0b8a36e7df3937ab7174 + uri: huggingface://unsloth/Ministral-3-8B-Instruct-2512-GGUF/Ministral-3-8B-Instruct-2512-Q4_K_M.gguf + - filename: llama-cpp/mmproj/mmproj-mistralai_Ministral-3-8B-Instruct-2512-f32.gguf + sha256: 242d11ff65ef844b0aac4e28d4b1318813370608845f17b3ef5826fd7e7fd015 + uri: huggingface://unsloth/Ministral-3-8B-Instruct-2512-GGUF/mmproj-F32.gguf +- !!merge <<: *mistral03 + name: "mistralai_ministral-3-8b-reasoning-2512-multimodal" + urls: + - https://huggingface.co/mistralai/Ministral-3-8B-Reasoning-2512 + - https://huggingface.co/unsloth/Ministral-3-8B-Reasoning-2512-GGUF + description: | + A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities. + + This model is the reasoning post-trained version, trained for reasoning tasks, making it ideal for math, coding and stem related use cases. + + The Ministral 3 family is designed for edge deployment, capable of running on a wide range of hardware. Ministral 3 8B can even be deployed locally, capable of fitting in 24GB of VRAM in BF16, and less than 12GB of RAM/VRAM when quantized. + + Key Features: + Ministral 3 8B consists of two main architectural components: + + + - 8.4B Language Model + - 0.4B Vision Encoder + + The Ministral 3 8B Reasoning model offers the following capabilities: + + + - Vision: Enables the model to analyze images and provide insights based on visual content, in addition to text. + - Multilingual: Supports dozens of languages, including English, French, Spanish, German, Italian, Portuguese, Dutch, Chinese, Japanese, Korean, Arabic. + - System Prompt: Maintains strong adherence and support for system prompts. + - Agentic: Offers best-in-class agentic capabilities with native function calling and JSON outputting. + - Reasoning: Excels at complex, multi-step reasoning and dynamic problem-solving. + - Edge-Optimized: Delivers best-in-class performance at a small scale, deployable anywhere. + - Apache 2.0 License: Open-source license allowing usage and modification for both commercial and non-commercial purposes. + - Large Context Window: Supports a 256k context window. + + This gallery entry includes mmproj for multimodality and uses Unsloth recommended defaults. + tags: + - llm + - gguf + - gpu + - mistral + - cpu + - function-calling + - multimodal + overrides: + context_size: 32768 + parameters: + model: llama-cpp/models/mistralai_Ministral-3-8B-Reasoning-2512-Q4_K_M.gguf + temperature: 0.7 + top_p: 0.95 + mmproj: llama-cpp/mmproj/mmproj-mistralai_Ministral-3-8B-Reasoning-2512-f32.gguf + files: + - filename: llama-cpp/models/mistralai_Ministral-3-8B-Reasoning-2512-Q4_K_M.gguf + sha256: c3d1c5ab7406a0fc9d50ad2f0d15d34d5693db00bf953e8a9cd9a243b81cb1b2 + uri: huggingface://unsloth/Ministral-3-8B-Reasoning-2512-GGUF/Ministral-3-8B-Reasoning-2512-Q4_K_M.gguf + - filename: llama-cpp/mmproj/mmproj-mistralai_Ministral-3-8B-Reasoning-2512-f32.gguf + sha256: 92252621cb957949379ff81ee14b15887d37eade3845a6e937e571b98c2c84c2 + uri: huggingface://unsloth/Ministral-3-8B-Reasoning-2512-GGUF/mmproj-F32.gguf +- !!merge <<: *mistral03 + name: "mistralai_ministral-3-3b-instruct-2512-multimodal" + urls: + - https://huggingface.co/mistralai/Ministral-3-3B-Instruct-2512 + - https://huggingface.co/unsloth/Ministral-3-3B-Instruct-2512-GGUF + description: | + The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities. + + The Ministral 3 family is designed for edge deployment, capable of running on a wide range of hardware. Ministral 3 3B can even be deployed locally, capable of fitting in 8GB of VRAM in FP8, and less if further quantized. + + Key Features: + Ministral 3 3B consists of two main architectural components: + + - 3.4B Language Model + - 0.4B Vision Encoder + + The Ministral 3 3B Instruct model offers the following capabilities: + + - Vision: Enables the model to analyze images and provide insights based on visual content, in addition to text. + - Multilingual: Supports dozens of languages, including English, French, Spanish, German, Italian, Portuguese, Dutch, Chinese, Japanese, Korean, Arabic. + - System Prompt: Maintains strong adherence and support for system prompts. + - Agentic: Offers best-in-class agentic capabilities with native function calling and JSON outputting. + - Edge-Optimized: Delivers best-in-class performance at a small scale, deployable anywhere. + - Apache 2.0 License: Open-source license allowing usage and modification for both commercial and non-commercial purposes. + - Large Context Window: Supports a 256k context window. + + This gallery entry includes mmproj for multimodality and uses Unsloth recommended defaults. + tags: + - llm + - gguf + - gpu + - mistral + - cpu + - function-calling + - multimodal + overrides: + context_size: 16384 + parameters: + model: llama-cpp/models/mistralai_Ministral-3-3B-Instruct-2512-Q4_K_M.gguf + temperature: 0.15 + mmproj: llama-cpp/mmproj/mmproj-mistralai_Ministral-3-3B-Instruct-2512-f32.gguf + files: + - filename: llama-cpp/models/mistralai_Ministral-3-3B-Instruct-2512-Q4_K_M.gguf + sha256: fd46fc371ff0509bfa8657ac956b7de8534d7d9baaa4947975c0648c3aa397f4 + uri: huggingface://unsloth/Ministral-3-3B-Instruct-2512-GGUF/Ministral-3-3B-Instruct-2512-Q4_K_M.gguf + - filename: llama-cpp/mmproj/mmproj-mistralai_Ministral-3-3B-Instruct-2512-f32.gguf + sha256: 57bb4e6f01166985ca2fc16061be4023fcb95cb8e60f445b8d0bf1ee30268636 + uri: huggingface://unsloth/Ministral-3-3B-Instruct-2512-GGUF/mmproj-F32.gguf +- !!merge <<: *mistral03 + name: "mistralai_ministral-3-3b-reasoning-2512-multimodal" + urls: + - https://huggingface.co/mistralai/Ministral-3-3B-Reasoning-2512 + - https://huggingface.co/unsloth/Ministral-3-3B-Reasoning-2512-GGUF + description: | + The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities. + + This model is the reasoning post-trained version, trained for reasoning tasks, making it ideal for math, coding and stem related use cases. + + The Ministral 3 family is designed for edge deployment, capable of running on a wide range of hardware. Ministral 3 3B can even be deployed locally, fitting in 16GB of VRAM in BF16, and less than 8GB of RAM/VRAM when quantized. + + Key Features: + Ministral 3 3B consists of two main architectural components: + + - 3.4B Language Model + - 0.4B Vision Encoder + + The Ministral 3 3B Reasoning model offers the following capabilities: + + - Vision: Enables the model to analyze images and provide insights based on visual content, in addition to text. + - Multilingual: Supports dozens of languages, including English, French, Spanish, German, Italian, Portuguese, Dutch, Chinese, Japanese, Korean, Arabic. + - System Prompt: Maintains strong adherence and support for system prompts. + - Agentic: Offers best-in-class agentic capabilities with native function calling and JSON outputting. + - Reasoning: Excels at complex, multi-step reasoning and dynamic problem-solving. + - Edge-Optimized: Delivers best-in-class performance at a small scale, deployable anywhere. + - Apache 2.0 License: Open-source license allowing usage and modification for both commercial and non-commercial purposes. + - Large Context Window: Supports a 256k context window. + + This gallery entry includes mmproj for multimodality and uses Unsloth recommended defaults. + tags: + - llm + - gguf + - gpu + - mistral + - cpu + - function-calling + - multimodal + overrides: + context_size: 32768 + parameters: + model: llama-cpp/models/mistralai_Ministral-3-3B-Reasoning-2512-Q4_K_M.gguf + temperature: 0.7 + top_p: 0.95 + mmproj: llama-cpp/mmproj/mmproj-mistralai_Ministral-3-3B-Reasoning-2512-f32.gguf + files: + - filename: llama-cpp/models/mistralai_Ministral-3-3B-Reasoning-2512-Q4_K_M.gguf + sha256: a2648395d533b6d1408667d00e0b778f3823f3f3179ba371f89355f2e957e42e + uri: huggingface://unsloth/Ministral-3-3B-Reasoning-2512-GGUF/Ministral-3-3B-Reasoning-2512-Q4_K_M.gguf + - filename: llama-cpp/mmproj/mmproj-mistralai_Ministral-3-3B-Reasoning-2512-f32.gguf + sha256: 8035a6a10dfc6250f50c62764fae3ac2ef6d693fc9252307c7093198aabba812 + uri: huggingface://unsloth/Ministral-3-3B-Reasoning-2512-GGUF/mmproj-F32.gguf - &mudler url: "github:mudler/LocalAI/gallery/mudler.yaml@master" ### START mudler's LocalAI specific-models name: "LocalAI-llama3-8b-function-call-v0.2"