turboderp
AI overview
Sign in and the AI will write an overview from our coverage.
Headlines · 1
- Reddit user: 1.66bpw exl3 quantization of Qwen3.8-Flash-Next runs under 36GB on one RTX 5090
A poster on r/LocalLLaMA (u/Unstable_Llama) reports that a 1.66 bit-per-weight exl3 quantization of Qwen3.8-Flash-Next fits entirely in a 36GB footprint on a single RTX 5090 with no offloaded experts. The poster describes inference as stable with no reasoning loops at roughly 200–300 tokens per second, but notes heavy compaction is needed because a 32GB GPU leaves little room for context even with cache quantization. The weights are said to be hosted on Hugging Face under turboderp/Qwen3.8-Flash-Next-exl3; the performance claims are the user's own and have not been independently verified.
r/LocalLLaMA · 🔥 0
Experience and discussion from the community
Share my turboderp experienceAsk about turboderp
Nobody has shared their experience with turboderp yet.