AI is happening. The future is updating.Qwen3.8-9B-Distill
> [!Note] > This repository contains model weights and configuration files in the Hugging Face Transformers format. > > These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, and other standard runtimes with Qwen3.5 architecture support. **Qwen3.8-9B** is a full-parameter distillation of **Qwen3.8 2.4T A95B** into the Qwen3.5-9B architecture. The student was trained on **~70,000 curated teacher traces** from our internal Qwen3.8 distillation datasets — dense chain-of-thought spanning mathematics, code, general reasoning, instruction following, and tool use, quality-filtered before training. The objective: bring the reasoning behavior of a frontier-scale teacher into a dense 9B that deploys on a single GPU.
> [!Note] > This repository contains model weights and configuration files in the Hugging Face Transformers format. > > These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, and other standard runtimes with Qwen3.5 architecture support. **Qwen3.8-9B** is a full-parameter distillation of **Qwen3.8 2.4T A95B** into the Qwen3.5-9B architecture. The student was trained on **~70,000 curated teacher traces** from our internal Qwen3.8 distillation datasets — dense chain-of-thought spanning mathematics, code, general reasoning, instruction following, and tool use, quality-filtered before training. The objective: bring the reasoning behavior of a frontier-scale teacher into a dense 9B that deploys on a single GPU.