Qwen3.8-Flash-Next has been officially released, introducing a 6B-active open...

Qwen3.8-Flash-Next has been officially released, introducing a 6B-active open model that surpasses Claude Opus 4.6 Max on eight out of nine standard benchmarks. The model applies a highly sparse Mixture of Experts (MoE) framework, featuring 125 billion overall parameters and 51 billion n-gram embeddings, with just 6 billion parameters active per token. Benchmark results include: • SWE-bench Pro: 62.5 • SWE-bench Multilingual: 81.0 • CoworkBench: 73.9 • JobBench: 55.7 • Toolathlon: 73.5 • IFBench: 81.3 • GPQA Diamond: 91.7 • LiveCodeBench: 91.9 Qwen3.8-Flash-Next also exceeds the performance of Qwen3.8-27B and DeepSeek-V4-Flash across the majority of evaluated categories. 📰 @aipost