Qwen 3.8 27B Performance Benchmarks Emerge Across Diverse Hardware
This story is from 2026-08-21. It is preserved in the archive; the latest stories are on the live feed.
Users report token generation speeds and optimization techniques for Qwen 3.8 27B on AMD, Apple, and Nvidia hardware, including a 7 tok/s Apple Neural Engine build and a 2.26x speculative decoding speedup via DFlash 2.
Read the full story at r/LocalLLaMA ↗
Timeline · 6 reports
- 2026-08-22 20:41 · r/LocalLLaMA
I benchmark DFlash 2 (PR build) in llama.cpp on Qwen 3.8 27B against all speculative methods for 3 days. 2.26x on 100 real coding prompts, 4.68x with one n-gram drafter on top. Up to 8x on specific cases. - 2026-08-22 12:16 · r/LocalLLM
Any of you running Qwen 3.8 27B on an RTX Pro 4000 SFF Blackwell? - 2026-08-22 04:48 · r/LocalLLM
people running Qwen 3.8 27B on apple silicon… whats your best token generation speed and how did you attain it? - 2026-08-21 19:58 · r/LocalLLaMA
Strix Halo (8060S / gfx1151), Qwen-3.8-27B @ Q8 and Q6 UD v3, up to 256K ctx, llama.cpp, DFlash2, vision, real workloads quality and steady performances, optimized recipes, ... - 2026-08-21 12:02 · r/LocalLLM
Running Qwen 3.8 27b FP16 on the Apple Neural Engine - 7 Watts of power to run a FP16 model @ 7 tok/s - 2026-08-21 09:25 · r/LocalLLM
Anyone running Qwen 3.8 27B Q3/Q4 on an RX 9060 XT 16GB using llama.cpp?