How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "philbert440/ThinkingCap-Qwen3.6-27B-Uncensored-Aggressive"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "philbert440/ThinkingCap-Qwen3.6-27B-Uncensored-Aggressive",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker
docker model run hf.co/philbert440/ThinkingCap-Qwen3.6-27B-Uncensored-Aggressive
Quick Links

ThinkingCap Qwen3.6 27B Uncensored Aggressive

Most-open tier on the ThinkingCap base β€” BF16 source checkpoint.

Part of the Qwen3.6-27B Uncensored β€” ThinkingCap collection β€” abliterated (Heretic) Qwen3.6 vision-language models served on Tesla V100 via 1Cat-vLLM.

What this is

Aggressive β€” heavy abliteration: the most open tier (openness 0.417, top of the family) with a modest reasoning cost.

BF16 β€” full-precision source checkpoint. Use for further quantization or on GPUs with headroom. The quantized siblings below carry the served benchmarks.

Base model: bottlecapai/ThinkingCap-Qwen3.6-27B

Openness

Openness profile (honest): abliteration opens up hacking / malware / lock-picking / NSFW / disinformation prompts; weapons, drugs, political persuasion, surveillance, and extremism stay refused across all tiers. "Uncensored" here means cyber/NSFW-permissive, not unconditionally open.

Variants

See the Qwen3.6-27B Uncensored β€” ThinkingCap collection for all tiers and formats (BF16 / W4A16-AWQ / NVFP4).


Abliteration removes safety refusals; you are responsible for lawful, ethical use.

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Model tree for philbert440/ThinkingCap-Qwen3.6-27B-Uncensored-Aggressive

Base model

Qwen/Qwen3.6-27B
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Collection including philbert440/ThinkingCap-Qwen3.6-27B-Uncensored-Aggressive