AI is happening. The future is updating.Qwen3.8-9B-Distill-GGUF
GGUF quantizations of **empero-ai/Qwen3.8-9B** — a full-parameter distillation of **Qwen3.8 2.4T A95B** into the Qwen3.5-9B architecture — for llama.cpp, Ollama, LM Studio, Jan, KoboldCpp, and other stock GGUF runtimes. This card is about choosing a file and running it. The capability writeup, full benchmark results, and best practices live on the **main model card**. Headline results for the source model (CoT protocols, `lm-evaluation-harness`, identical settings base vs. student):
GGUF quantizations of **empero-ai/Qwen3.8-9B** — a full-parameter distillation of **Qwen3.8 2.4T A95B** into the Qwen3.5-9B architecture — for llama.cpp, Ollama, LM Studio, Jan, KoboldCpp, and other stock GGUF runtimes. This card is about choosing a file and running it. The capability writeup, full benchmark results, and best practices live on the **main model card**. Headline results for the source model (CoT protocols, `lm-evaluation-harness`, identical settings base vs. student):