SemiAnalysis(@SemiAnalysis_):Congrats to @Alibaba_Qwen on the release of Qwen3.8-Flash-Next, using the same architecture innovations as their upcoming Qwen4 model! Such innovations include: 🟠 51-billion-param N-gram Embedding to look up a table with very little extra computation, which means the embedding table can be offloaded to slower & less expensive tiers of DRAM 🟠 Gated Residual (GR): it seems like a lot of Chinese labs are now innovating on the res connections, like Kimi's AttentionRes and DeepSeek's mHC 🟠 Qwen Sparse Attention (QSA): lightning indexer to select context at micro-block granularity Glad to see great Chinese open innovations along with end-to-end model weights to show these innovations can compose well together!

2026.08.26 19:00

Congrats to @Alibaba_Qwen on the release of Qwen3.8-Flash-Next, using the same architecture innovations as their upcoming Qwen4 model! Such innovations include: 🟠 51-billion-param N-gram Embedding to look up a table with very little extra computation, which means the embedding table can be offloaded to slower & less expensive tiers of DRAM 🟠 Gated Residual (GR): it seems like a lot of Chinese labs are now innovating on the res connections, like Kimi's AttentionRes and DeepSeek's mHC 🟠 Qwen Sparse Attention (QSA): lightning indexer to select context at micro-block granularity Glad to see great Chinese open innovations along with end-to-end model weights to show these innovations can compose well together!