Qwen3.8-Flash-Next Gains Rapid Local Inference Support
This story is from 2026-08-26. It is preserved in the archive; the latest stories are on the live feed.
Qwen's new multimodal MoE model, Qwen3.8-Flash-Next, is being rapidly adopted by local inference tools, with llama.cpp support merged and community benchmarks showing 25-400 tokens per second across various hardware.
Read the full story at r/LocalLLM ↗
Timeline · 10 reports
- 2026-08-28 10:55 · r/LocalLLaMA
Qwen3.8-Flash-Next (UD-IQ4_XS) on 2x RTX 3060 + 7800X3D, from initial 36 tps prefill to 400 tps and other benchmarks (-sm tensor trap) + VRAM/RAM usage - 2026-08-28 02:25 · r/LocalLLM
Running Qwen3.8-Flash-Next at Full 262K Context on a 128GB MacBook - 2026-08-27 22:30 · r/LocalLLM
Unsloth Qwen 3.8 Flash Next 4bit = 25 tok/s - 2026-08-27 21:59 · r/LocalLLM
EngramHalo.cpp: Qwen 3.8 Flash-Next on Strix Halo — 23.5 → 39 tok/s, working MTP, 27 GB engram table on SSD - 2026-08-27 19:34 · r/LocalLLaMA
llama.cpp support for Qwen3.8-Flash-Next has been merged - 2026-08-27 12:34 · r/LocalLLaMA
Qwen3.8-Flash-Next: Time to Update Those Benchmarks - 2026-08-26 23:52 · Simon Willison's Weblog
Qwen3.8-Flash-Next - 2026-08-26 21:11 · r/LocalLLM
Qwen3.8 flash next on 4x v100s - 2026-08-26 18:46 · r/LocalLLM
Qwen3.8-Flash-Next (125B-A6B) running on Strix Halo 128gb: 23 t/s decode, 390 t/s prefill, built from the llama.cpp PR - 2026-08-26 18:10 · r/LocalLLM
Qwen3.8-Flash-Next MoE 125B A6B But