How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nesymerp1/Gemma-4-Dark-Thoughts-V2-31B-Q4_K_M-Q5_K_S"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nesymerp1/Gemma-4-Dark-Thoughts-V2-31B-Q4_K_M-Q5_K_S",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/nesymerp1/Gemma-4-Dark-Thoughts-V2-31B-Q4_K_M-Q5_K_S:Q4_K_M
Quick Links

This is a quantization of https://huggingface.co/Ateron/Gemma-4-Dark-Thoughts-V2-31B using llamacpp's llama-quantize.exe feuture.

This is ment to be used as fallback quantizations, specifically relief for those who are waiting for other quanters to upload.

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Model size
31B params
Architecture
gemma4
Hardware compatibility
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