Qwen3.8-Flash ships with local deployment and claims SWE-bench Pro win over Claude

Alibaba Qwen released Qwen3.8-Flash (later Qwen3.8-Flash-Next), an open-weight multimodal MoE model on a new "Next" architecture, widely seen as a preview of Qwen4. Unsloth enabled local running with just 75GB RAM and shipped 1-4bit GGUF quantizations, recommending llama.cpp. Community tests report 62.5 on SWE-bench Pro, beating Claude Opus 4.6 Max's 53.4 at roughly 1/9 the inference cost.Confirmed - 125B total parameters, multimodal MoE with only 6B active parameters per token - 51B N-gram Embedding attached to the main model (per @AGI Hunt) - Unsloth local deployment (75GB RAM) and 1-4bit GGUF quantizations via llama.cpp (also relayed by @MaziyarPanahi) - @Hesamation tested 62.5 on SWE-bench Pro vs Claude Opus 4.6 Max's 53.4Unconfirmed - Benchmark scores and the "1/9 cost" claim come from the vendor and community relays; no independent verification yet - @Hesamation says the model previews Qwen4 architecture; official Qwen4 details remain unknownWhy it matters - An open-weights model claims to beat top closed-source models on a real engineering benchmark at a fraction of the cost - Sparse MoE plus extreme quantization makes a 125B-class model locally deployable on consumer/workstation hardware

2026-08-26 ~ 2026-08-28 · 5 related posts

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