Wësche(@WescheNex1q):Sparkbench local battle: Qwen3.8-Flash-Next (NVFP4 TP2, spec off) scored 87.0 GLM-5.3-Flash (NVFP4 TP2, DFlash2) at 85.7 This is a deployment comparison, not a universal model ranking, but Qwen was faster, more reliable, and cleaner here. The most interesting result wasn’t the score: GLM hit four ~261K-token repetition loops, while Qwen’s NEXTN path had its own collapse and had to be disabled Local inference moves fast, but serving-stack correctness matters as much as the model. Full deployment and results:

2026.08.29 16:56

Sparkbench local battle: Qwen3.8-Flash-Next (NVFP4 TP2, spec off) scored 87.0 GLM-5.3-Flash (NVFP4 TP2, DFlash2) at 85.7 This is a deployment comparison, not a universal model ranking, but Qwen was faster, more reliable, and cleaner here. The most interesting result wasn’t the score: GLM hit four ~261K-token repetition loops, while Qwen’s NEXTN path had its own collapse and had to be disabled Local inference moves fast, but serving-stack correctness matters as much as the model. Full deployment and results: