🌟 Qwen3.5 2B Claude 4.6 Opus Reasoning Distilled 📢 Announcement Update: This model has been further enhanced with additional reasoning data distilled from Qwen3.5 27B . The new training data introduces higher quality reasoning trajectories across domains such as science, instruction following, and mathematics . Part of the data comes from Jackrong/Qwen3.5 reasoning 700x , a curated dataset designed to improve structured step by step reasoning and reasoning diversity . 💡 Model Introduction Qwen3.5 2B Claude 4.6 Opus Reasoning Distilled is a highly capable reasoning model fine tuned on top of the Qwen3.5 2B dense architecture. The model's core directive is to leverage state of the art Chain of Thought (CoT) distillation primarily sourced from Claude 4.6 Opus interactions. Through Supervised Fine Tuning (SFT) focusing specifically on structured reasoning logic, this model excels in breaking down complex user problems, planning step by step methodologies within strictly formatted tags, and ultimately delivering precise, nuanced solutions. 🗺️ Training Pipeline Overview 🧠 Example of Learned Reasoning Scaffold（Example） The model includes targeted optimizations addressing Qwen3.5’s te…
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