Produced by Antigma Labs, Antigma Quantize Space

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Antigma's GitHub Homepage https://github.com/AntigmaLabs

llama.cpp quantization

Using llama.cpp release b5223 for quantization. Original model: https://huggingface.co/unsloth/Devstral-Small-2505 Run them directly with llama.cpp, or any other llama.cpp based project

Prompt format

<|begin▁of▁sentence|>{system_prompt}<|User|>{prompt}<|Assistant|><|end▁of▁sentence|><|Assistant|>

Download a file (not the whole branch) from below:

Filename Quant type File Size Split
devstral-small-2505-q2_k.gguf Q2_K 8.28 GB False
devstral-small-2505-q3_k_l.gguf Q3_K_L 11.55 GB False
devstral-small-2505-q6_k.gguf Q6_K 18.02 GB False
devstral-small-2505-q4_k_m.gguf Q4_K_M 13.35 GB False
devstral-small-2505-q5_k_m.gguf Q5_K_M 15.61 GB False
devstral-small-2505-q8_0.gguf Q8_0 23.33 GB False

Downloading using huggingface-cli

Click to view download instructions First, make sure you have hugginface-cli installed:
pip install -U "huggingface_hub[cli]"

Then, you can target the specific file you want:

huggingface-cli download https://huggingface.co/Antigma/Devstral-Small-2505-GGUF --include "devstral-small-2505-q2_k.gguf" --local-dir ./

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:

huggingface-cli download https://huggingface.co/Antigma/Devstral-Small-2505-GGUF --include "devstral-small-2505-q2_k.gguf/*" --local-dir ./

You can either specify a new local-dir (deepseek-ai_DeepSeek-V3-0324-Q8_0) or download them all in place (./)

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GGUF
Model size
23.6B params
Architecture
llama
Hardware compatibility
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