GLM-5.1 Local Inference Tops 40 TPS

This looks less like a model breakthrough than a serving-stack signal: GLM-5.1 is already strong, but the real unlock is runtime tuning on serious local hardware. That makes the post interesting for teams chasing practical self-hosted agent performance.

• –The prefill numbers are the headline here, because long-context coding sessions live or die on prompt ingestion speed as much as decode speed.
• –The sglang patching detail suggests the software ecosystem is still leaving performance on the table for RTX 6000-class cards.
• –Four workstation GPUs at a 350W cap is a deployable setup, which matters more than synthetic leaderboard bragging for real users.
• –The “close to Sonnet + Claude Code” comparison is a useful signpost: open-weights local agent stacks are inching toward premium hosted UX.
• –GLM-5.1 already has official local-serving support across SGLang, vLLM, xLLM, Transformers, and KTransformers, so this post is about optimization maturity, not basic feasibility.