Qwen3.5-9B R7 Research Vision (Q4_K_M)

Fine-tuned Qwen3.5-9B with distilled reasoning and full vision support. 883 tensors (427 text + 441 vision + 15 MTP) — vision tower preserved byte-for-byte from base via llama-export-lora merge.

Capabilities

• Vision — image understanding (reads text, describes scenes, answers visual questions)
• Thinking — structured reasoning in <think> blocks
• Tool calling — structured tool_calls via Ollama /api/chat
• Instruction following — concise answers, format constraints, system prompt adherence

Eval Results

Training

• Base model: Qwen/Qwen3.5-9B
• Method: LoRA SFT (r=32, alpha=64, LR=1e-4, 1 epoch), merged via llama-export-lora to preserve vision
• Data: Additive mix of 4043 samples from:
  • bespokelabs/Bespoke-Stratos-17k — DeepSeek-R1 reasoning traces
  • allenai/tulu-3-sft-mixture — instruction diversity
  • Open-Orca/SlimOrca — curated GPT-4 instructions
  • PrimeIntellect/SYNTHETIC-1-SFT-Data — verified math/code/STEM
• Vision preservation: LoRA filtered (linear_attn removed) -> convert_lora_to_gguf -> llama-export-lora into base Q4_K_M GGUF. All 441 vision tensors + 15 MTP tensors unchanged.
• Training suite: robit-man/fine_tuning_suite

Quickstart

ollama run robit/qwen3.5-9b-r7-research-vision:q4km

Image chat

IMG64=$(base64 -w0 path/to/image.jpg)
curl -s http://localhost:11434/api/chat \
  -d '{"model":"robit/qwen3.5-9b-r7-research-vision:q4km","messages":[{"role":"user","content":"Describe this image.","images":["'"$IMG64"'"]}]}'

Parameters

• RENDERER qwen3.5 + PARSER qwen3.5 (enables tool calling + vision)
• num_ctx 262144 (max context)
• temperature 0.6, top_p 0.95
• stop "<|im_end|>"

License

Derived from Qwen3.5-9B (Apache 2.0). Training data licenses vary by source.