How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LuffyTheFox/Qwen3.8-27B-Unleashed-SSMFIX-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LuffyTheFox/Qwen3.8-27B-Unleashed-SSMFIX-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'
Use Docker
docker model run hf.co/LuffyTheFox/Qwen3.8-27B-Unleashed-SSMFIX-GGUF:
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This is Qwen3.8-27B-Unleashed-GGUF

made by outsourc-e with fixed by me scale for ssm_conv1d.weight tensors:

Tensor QType α/δ/σ̄ S_b S_a
blk.52.ssm_conv1d.weight F32 α=0.59005 0.0016 0.0006
blk.53.ssm_conv1d.weight F32 α=0.55484 0.0015 0.0005
blk.56.ssm_conv1d.weight F32 α=0.54486 0.0015 0.0004
blk.57.ssm_conv1d.weight F32 α=0.53574 0.0015 0.0004
blk.58.ssm_conv1d.weight F32 α=0.60972 0.0012 0.0005
blk.60.ssm_conv1d.weight F32 α=0.48136 0.0017 0.0004
blk.61.ssm_conv1d.weight F32 α=0.65327 0.0010 0.0004
blk.62.ssm_conv1d.weight F32 α=0.61856 0.0013 0.0005

α is optimal value for tensor scaling,

S_b tensor saturation before scaling,

S_a tensor saturation after scaling

Genesis SVD with Noise Gate supression can't be applied to this model, because it can process only BF16, F32, MXFP4, Q8_0 and Q4_0 tensors. NVFP4 encoding is not supported in gguf-py in llama.cpp. I can read NVFP4 weights, but can't modify them. So I fixed only 6 too loud ssm_conv1d.weight layers in this model. Everything else left unchanged.

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GGUF
Model size
27B params
Architecture
qwen35
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