GLM-5.3, a new open-source language model from Chinese startup z.ai, has launched on API at $1.40 per million input tokens and $4.40 per million output tokens—the same price as its predecessor.
The model drew attention for detecting a previously unknown vulnerability in Cursor, and z.ai plans eventually to release the weights openly, though timing and licensing details remain unclear.
What happened
GLM-5.3, a new open-source language model from Chinese startup z.ai, is now available via API following its debut last week. Developers with a GLM Coding Plan subscription can access it through an OpenAI Chat Completions-compatible protocol. Pricing matches the previous GLM-5.2 generation: $1.40 per million input tokens and $4.40 per million output tokens, with cached input at $0.26 per million tokens and free cached-input storage for a limited time.
Why it matters
The model gained attention for advanced cyber capabilities that reportedly uncovered a previously undetected vulnerability in Cursor. By keeping API pricing flat between generations, z.ai removes a cost barrier for developers considering migration from competitors, potentially lowering adoption friction during the transition.
What to watch
Z.ai said it plans to make the model's weights openly available, though a precise date and licensing terms have not yet been announced. This open-source release could further broaden access beyond API consumers.
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GLM-5.3 arrives at a moment when z.ai is working to establish its open-source language model in a competitive landscape dominated by established players. The model's reported ability to detect a previously undetected vulnerability in Cursor—a code editor—signals meaningful capability in specialized domains, which can drive adoption among developers building security-focused or code-related applications.
By maintaining the same per-token pricing as GLM-5.2, z.ai removes a potential friction point for developers evaluating whether to migrate from other models. In a market where token costs influence the unit economics of AI applications, pricing parity between generations lowers the switching barrier. The addition of free cached-input storage (for a limited time) further sweetens the offer for high-volume or repeated-query workloads.
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