GLM 5.2 hands-on: the first open-weights model that feels like Opus and GPT, and why inference margins are next to collapse

GLM 5.2 and the coming AI margin collapse

The author used GLM 5.2 as a daily driver for two weeks and found it nearly indistinguishable from Claude Opus for most tasks. Switching is trivial—just point the API base URL to a compatible endpoint and it runs inside Claude Code. Two real gaps: no vision support, and the built-in web search is slow and poor, which hurts agentic workflows that rely on images or live lookups. Inference pricing sits around $4.40/MTok, under 20% of Opus’s retail rate; even with heavier token usage, costs drop by more than half. The post argues that frontier labs’ ~90% inference gross margin is unsustainable once open-weights models hit this quality bar.

Why it matters: The author ran GLM 5.2 as a daily driver for two weeks and provides a reproducible swap path plus pricing—this isn't a press release. Two limits keep it at 78: the test covers only coding workflows, and the vision/search gaps narrow the claim's reach. It's a single-blog experi...