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 b4944 for quantization. Original model: https://huggingface.co/Qwen/Qwen3-0.6B-Base 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
qwen3-0.6b-base-q4_k_m.gguf Q4_K_M 0.37 GB False
qwen3-0.6b-base-q4_0.gguf Q4_0 0.36 GB False
qwen3-0.6b-base-q4_k_s.gguf Q4_K_S 0.36 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/Qwen3-0.6B-Base-GGUF --include "qwen3-0.6b-base-q4_k_m.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/Qwen3-0.6B-Base-GGUF --include "qwen3-0.6b-base-q4_k_m.gguf/*" --local-dir ./

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

Downloads last month
4
GGUF
Model size
596M params
Architecture
qwen3
Hardware compatibility
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4-bit

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