Run GLM-5.3 in the EU for coding and long agent tasks

GLM-5.3 was announced by Z.ai, formerly Zhipu AI, in August 2026, with full weights published about two weeks later. It uses the same base model as GLM-5.2, a large mixture-of-experts network of roughly 753 billion parameters in the published checkpoint; every improvement in 5.3 comes from post-training.

Z.ai's documentation describes it as text-only, with a one-million-token context window and up to 128K output tokens. It always reasons before answering, with three effort levels: low, high and max. Z.ai reports a 50 per cent gain over GLM-5.2 on its internal coding benchmark and positions GLM-5.3 as its model for complex programming and long tasks.

GLM-5.3 is at its best in long coding sessions: working through a large repository, running commands, reading failures and iterating until tests pass. The one-million-token window keeps long tool histories in view. Z.ai also reports strong results in security research tasks such as vulnerability discovery, which is useful for defensive teams and calls for sensible access controls.

It is a very large model, so it is the wrong tool for short chat or simple extraction. Reasoning cannot be switched off, which adds output tokens even to easy requests; use the low effort level for those. It does not read images; GLM-5.3-Flash is the multimodal sibling. The model card lists English and Chinese as its main languages.

inference.eu offers both the OpenAI and the Anthropic request formats. For OpenAI-style tools, set the base URL to the inference.eu API, use your inference.eu key and set the model to glm-5.3. For Claude Code and other Anthropic-format tools, use our Anthropic-compatible endpoint with the same model name.

Pass reasoning_effort as low, high or max; Z.ai's default is max. For chat-style use, Z.ai recommends clearing earlier thinking from the history so the context does not fill with old reasoning. Tool calls and streaming work as usual. Set a generous max_tokens for agent steps that plan or write large changes.

GLM-5.3 is developed in China, but on inference.eu its open weights run on infrastructure in the European Union. Your prompts, source code and the model's responses are processed in EU data centres, are not sent to Z.ai, and are never used to train any model.

Every customer receives a data processing agreement under Article 28 of the GDPR and our subprocessor list, which your security team can review before rollout. Billing is in euros. The GLM-5.3 licence is permissive for most users: it grants broad rights to use, modify and sell, and only asks model-as-a-service operators with more than 10 billion US dollars in annual revenue to pass a security review by Z.ai.