
Qwen3.8-Flash-Next
Open-weights preview of the Qwen4 architecture — 6B active, extreme sparsity.
About
Qwen3.8-Flash-Next, released August 26, 2026, is Alibaba's open-weights preview of the architecture that will underpin Qwen4. The headline reads 125B with 6B activated, but the full checkpoint is roughly 180B: a 125B transformer stack, a 51B n-gram embedding table that lives in host RAM via row lookups, and a 4B multi-token-prediction head. It combines Gated DeltaNet linear attention with a sparse-retrieval mechanism (Qwen Sparse Attention), a 512-expert MoE with a gated shared expert, and Muon-optimizer training. Native context is 262,144 tokens, extensible toward 1M. Alibaba reports 62.5 on SWE-bench Pro from its own agent-harness runs and claims training cost roughly one-ninth of Qwen3.7-Plus.
The honest picture: all headline numbers are vendor-supplied, and the model is explicitly experimental — an architecture preview, not a finished Qwen4 product. The checkpoint is heavy (360GB full, ~186GB FP8), so single-consumer-GPU inference is unrealistic despite the 6B-active headline. The Qwen Community License 1.0 is free for most uses but requires a separate agreement to sell model-as-a-service access.
Specs
Context window
Pricing
Free quota
API access
Weights
Released
Benchmarks
Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.
Use cases
Trust score — 9/10
Scored 9/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 58; Trending score 92/100 from researcher assessment.
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