How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "prithivMLmods/Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0-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": "prithivMLmods/Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0-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/prithivMLmods/Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0-GGUF:
Quick Links

Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0-GGUF

Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0 is a reasoning-capable 2B-parameter language model built on top of Qwen/Qwen3.5-2B. The model was trained using a multi-stage supervised fine-tuning (SFT) pipeline on approximately 6,000 coding and STEM-focused Opus reasoning traces, along with additional high-quality reasoning traces, to improve long-form reasoning, coding, mathematical problem solving, scientific analysis, and instruction-following capabilities.

This model is an experimental release and may generate unexpected behaviors or reasoning artifacts in certain scenarios.

Model Files

File Name Quant Type File Size File Link
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.BF16.gguf BF16 3.78 GB Download
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.F16.gguf F16 3.78 GB Download
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.Q3_K_L.gguf Q3_K_L 1.16 GB Download
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.Q3_K_M.gguf Q3_K_M 1.1 GB Download
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.Q3_K_S.gguf Q3_K_S 1.02 GB Download
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.Q4_K_M.gguf Q4_K_M 1.27 GB Download
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.Q4_K_S.gguf Q4_K_S 1.21 GB Download
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.Q5_K_M.gguf Q5_K_M 1.41 GB Download
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.Q5_K_S.gguf Q5_K_S 1.37 GB Download
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.Q6_K.gguf Q6_K 1.56 GB Download
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.Q8_0.gguf Q8_0 2.01 GB Download
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.mmproj-bf16.gguf mmproj-bf16 671 MB Download
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.mmproj-f16.gguf mmproj-f16 671 MB Download
Qwen3.5-2B-Opus-Distilled-Heretic-Thinking-Multistage-SFT-v1.0.mmproj-q8_0.gguf mmproj-q8_0 365 MB Download

llama.cpp

LLM inference in C/C++ — https://github.com/ggml-org/llama.cpp

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GGUF
Model size
2B params
Architecture
qwen35
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