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Qwen3.8-Flash-Next Runs on Consumer GPUs, But Engine Performance Varies

This story is from 2026-08-27. It is preserved in the archive; the latest stories are on the live feed.

Llama.cpp merged support for Qwen3.8-Flash-Next, enabling GGUF quantized runs on consumer hardware, with reports of 55 t/s on 4x3090 and 400 tps on 2x3060 after tuning. However, vLLM is about 4x faster at long context, and llama.cpp struggles with agentic workloads.

Read the full story at r/LocalLLaMA ↗

Timeline · 4 reports

  1. 2026-08-29 14:47 · r/LocalLLM
    Qwen3.8-Flash-Next IQ1_S on a single 5070 (12GB VRAM)
  2. 2026-08-29 08:25 · r/LocalLLM
    Qwen3.8-Flash-Next (qwen4exp): llama.cpp isn't ready for agentic work, vLLM is ~4x faster at long context (RTX PRO 6000, full numbers)
  3. 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
  4. 2026-08-27 19:34 · r/LocalLLaMA
    llama.cpp support for Qwen3.8-Flash-Next has been merged

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