GLM-5.3 Model Overview & Integration Guide

DeepInfra’s integration guide presents Z.ai’s GLM-5.3 as an open-weights reasoning model for software engineering, agentic workflows, and cybersecurity tasks, offering text input and output with a 1,048,576-token context window and served by DeepInfra in fp4 under a zero-retention policy. Built on the same base as GLM-5.2, the model’s reported improvements stem from post-training, with Z.ai claiming substantial gains in coding, cyber evaluations, and token efficiency; its published benchmark results show broad improvement over GLM-5.2, while closed models such as GPT-5.6 Sol remain ahead on several tests. The guide cautions that benchmark results use Z.ai’s own evaluation setup and that cited throughput figures do not represent DeepInfra service performance. Pricing currently includes a 25% promotional discount, with a lower-cost Flex tier for retryable, non-real-time work that may queue for up to ten minutes. GLM-5.3 is accessible through an OpenAI-compatible chat-completions API, supports reasoning controls, structured output, streaming, function calling, and standard sampling parameters, although most outputs are capped at 16,384 tokens despite the much larger total context window.

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