How to use from
SGLang
Install from pip and serve model
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "prithivMLmods/Qwen3.6-27B-abliterated-rMAX-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prithivMLmods/Qwen3.6-27B-abliterated-rMAX-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 images
docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "prithivMLmods/Qwen3.6-27B-abliterated-rMAX-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prithivMLmods/Qwen3.6-27B-abliterated-rMAX-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"
						}
					}
				]
			}
		]
	}'
Quick Links

Qwen3.6-27B-abliterated-rMAX-GGUF

Qwen3.6-27B-Abliterated-rMAX is an abliterated evolution built on top of Qwen/Qwen3.6-27B. This model applies advanced refusal direction analysis and ablation-based training strategies to reduce internal refusal behaviors while preserving the reasoning and instruction-following strengths of the original architecture. The result is a powerful 27B parameter language model optimized for detailed responses and improved instruction adherence.

model > prithivMLmods/Qwen3.6-27B-abliterated-rMAX

Model Files

File Name Quant Type File Size File Link
Qwen3.6-27B-abliterated-rMAX.BF16.gguf BF16 53.8 GB Download
Qwen3.6-27B-abliterated-rMAX.F16.gguf F16 53.8 GB Download
Qwen3.6-27B-abliterated-rMAX.F32.gguf F32 108 GB Download
Qwen3.6-27B-abliterated-rMAX.Q8_0.gguf Q8_0 28.6 GB Download
Qwen3.6-27B-abliterated-rMAX.mmproj-bf16.gguf mmproj-bf16 931 MB Download
Qwen3.6-27B-abliterated-rMAX.mmproj-f16.gguf mmproj-f16 931 MB Download
Qwen3.6-27B-abliterated-rMAX.mmproj-f32.gguf mmproj-f32 1.84 GB Download
Qwen3.6-27B-abliterated-rMAX.mmproj-q8_0.gguf mmproj-q8_0 629 MB Download

Quants Usage

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png

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GGUF
Model size
27B params
Architecture
qwen35
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