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GLM-5.3

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glm-5.3
Model Type GLM-5.3Flash

GLM-5.3 is the new flagship of the GLM-5 series from Z.ai (Zhipu), built for coding, agentic workflows and complex reasoning, with dependable Chinese and English writing. It always thinks before it answers, with the reasoning in reasoning_content, and it supports tool calling and streaming. Fully OpenAI-compatible: set model to glm-5.3. Pay-as-you-go, failed calls never billed, and cached input settles at the cache rate.

ChatCodingAgentsThinking modeOpenAI compatible
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Try out GLM-5.3 right here (available after login).

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About GLM-5.3

GLM-5.3 is the new flagship of the GLM-5 series from Z.ai (Zhipu), built for coding, agentic workflows and complex reasoning, and served on NezhaGate through the OpenAI-compatible API. It always thinks before it answers: the reasoning comes back in message.reasoning_content and the answer in content, so clients that only read content need no changes. Tool calling (function calling) and streaming are supported, and cached input settles at the cache rate. Set model to glm-5.3; pay-as-you-go, failed calls never billed.

Use cases

Coding assistant

Code generation, refactoring, explanation and review; it reasons before answering, which suits programming tasks that need several steps.

Agent workflows

OpenAI-format tool calling plugs into agent frameworks for retrieval, function calls and multi-step planning.

Chinese and English writing

Copy, reports, email and translation with natural Chinese phrasing, for content aimed at audiences in China and abroad.

Complex Q&A and analysis

Analysis, comparison and decision questions that need a chain of reasoning, which you can inspect in reasoning_content.

How to choose

Choose GLM-5.3 for stronger coding, agent and reasoning work, and GLM-5.3 Flash when the tasks are simple, high-volume and cost-sensitive. Both belong to the GLM-5.3 family, so switching is just the model field.

FAQ

Can I turn thinking off?
No. GLM-5.3 always thinks before it answers, and the reasoning tokens are billed at the output rate inside usage.completion_tokens. For shorter, cheaper replies, ask for concise answers in the prompt or switch to GLM-5.3 Flash.
How is it different from GLM-5.3 Flash?
GLM-5.3 is the flagship, stronger at coding, agents and complex reasoning; Flash is lighter with a lower unit price, suited to high-volume, simpler tasks. Both are called exactly the same way.
What happens with a very small max_tokens?
Reasoning tokens count as output. Upstream treats a max_tokens below 1024 as 1024; if reasoning uses the whole budget, content can come back empty with finish_reason length, and you are billed for the actual tokens in usage. Leave max_tokens at 1024 or more.
Does it support tool calling and streaming?
Yes to both. tools / tool_calls use the OpenAI format; with stream=true the reply arrives as SSE chunks and the reasoning streams in delta.reasoning_content.
Am I charged for failed calls?
No. Only calls that return normally are settled, at actual usage; upstream errors and timeouts never touch your balance.

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