Qwen3.5 Claude Opus distill gets v2

This is a smart local-model move: instead of chasing bigger parameter counts, it tries to make smaller Qwen3.5 models reason more economically, which is exactly what agent loops and consumer GPUs care about.

• –The release leans on 14,000+ Claude Opus-style samples, so the pitch is better reasoning scaffolding rather than just another generic fine-tune
• –The reported gains focus on fewer thinking tokens plus better HumanEval/HumanEval+ scores, which is the right tradeoff if you care about latency and cost
• –The author explicitly warns broad general-purpose capability may slip a bit, so this looks more like a specialist reasoning upgrade than a universal model
• –The 9B and 4B sizes make it practical for local deployment today, but the community’s obvious next question is still the missing 27B v2
• –Benchmark claims are still self-reported, so independent evals will matter before anyone crowns it a new local king