ngxson has shown that the original mmproj from Mistral Small 3.1 works seamlessly with Devstral Small, so the mmproj file is here for vision use! Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:
Input Text→ Output Text
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Input Text · Image→ Output Text
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Input Text→ Output Text
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Input Text→ Output Text
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View details ↗All quants made using imatrix option with dataset from here combined with a subset of combined_all_small.parquet from Ed Addario here Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:
Input Text · Image→ Output Text
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Text · Image→ Output Text
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View details ↗Original model: https://huggingface.co/mistralai/Ministral-3-3B-Instruct-2512-BF16 All quants made using imatrix option with dataset from here combined with a subset of combined_all_small.parquet from Ed Addario here Run them directly with llama.cpp, or any other llama.cpp based project
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗All quants made using imatrix option with dataset from here combined with a subset of combined_all_small.parquet from Ed Addario here Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗All quants made using imatrix option with dataset from here combined with a subset of combined_all_small.parquet from Ed Addario here Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (mistralai_Mistral-Small-3.1-24B-Instruct-2503-Q8_0) or download them all in place (./)
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Original model: https://huggingface.co/mistralai/Mistral-Small-3.2-24B-Instruct-2506 All quants made using imatrix option with dataset from here Run them directly with llama.cpp, or any other llama.cpp based project
Input Text · Image→ Output Text
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View details ↗All quants made using imatrix option with dataset from here - llama.cpp - LM Studio - koboldcpp - Jan AI - Text Generation Web UI - LoLLMs Note: if it's a newly supported model, you may need to wait for an update from the developers.
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (mistralai_Voxtral-Mini-3B-2507-Q8_0) or download them all in place (./)
Input Audio · Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (mistralai_Voxtral-Small-24B-2507-Q8_0) or download them all in place (./)
Input Audio · Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (mlabonne_gemma-3-12b-it-abliterated-Q8_0) or download them all in place (./)
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (mlabonne_gemma-3-27b-it-abliterated-Q8_0) or download them all in place (./)
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (mlabonne_gemma-3-4b-it-abliterated-Q8_0) or download them all in place (./)
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
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