GLM-5.3

glm-5.3
Open sourceGLM series

Overview

1M ContextCode generationAgentic tasksReasoning

GLM-5.3 is the strongest open-source model for coding released by Zhipu. It shares the base model and parameter scale of GLM-5.2 (743B total parameters), with every capability gain coming from extreme post-training scaling. It breaks new ground on complex software engineering, terminal operations and long-horizon agent tasks, with coding capability 50% higher than GLM-5.2; it also fills in cybersecurity, performing strongly on defensive security tasks such as white-box code review and vulnerability discovery. Combined with a million-token context, tiered thinking effort, function calling and MCP tools, it can drive project-scale software development, security audits and complex automation pipelines.

Million-token context
A 1M-token context window loads project-scale codebases and very long documents in a single pass.
Coding leap
Coding capability is 50% higher than GLM-5.2, ranking first among open-source models on complex software engineering and terminal operations.
Cybersecurity
White-box code review and vulnerability discovery, with strong results on defensive security tasks.
Post-training scaling
The IndexShare / SAO / Slime frameworks keep raising the intelligence ceiling on the same base model.

Features

Reasoning
Streaming
Tool calling
Context caching
Structured output
Web search
Batch
Prefix completion
Fine-tuning

Pricing

Input¥8/M tokens
Input (cache hit)¥2/M tokens
Output¥28/M tokens

Rate Limits & Context

Context Window1M
Max Output128K
RPM (requests/min)200
TPM (tokens/min)3M

Built-in Tools

web_search
Responses API
code_interpreter
Responses API
web_extractor
Responses API

API Reference

ENDPOINT
POST https://api.tokenfab.cn/v1/chat/completions

Request Example

curl https://api.tokenfab.cn/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOKENFAB_API_KEY" \
  -d '{
    "model": "glm-5.3",
    "thinking": { "type": "enabled" },
    "reasoning_effort": "max",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "请审查以下 Python 代码中的安全漏洞,并给出修复建议。"}
    ]
  }'

Response Example

JSON
{
  "id": "chatcmpl-glm53-9d2k7f1",
  "object": "chat.completion",
  "created": 1784950000,
  "model": "glm-5.3",
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "审查发现两处风险:1) 用户输入未做参数化处理,存在 SQL 注入隐患;2) 敏感信息以明文写入日志。建议改用预编译语句并脱敏后落盘。"
    },
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 42,
    "completion_tokens": 156,
    "total_tokens": 198
  }
}

Request Parameters

ParameterTypeRequiredDescription
modelstringModel ID, set to glm-5.3
messagesarrayList of chat messages, each with role and content
thinkingobjectThinking configuration, {"type":"enabled"} (enabling only; disabling is not supported)
reasoning_effortenumThinking effort: low / high / max, default max
temperaturefloatSampling temperature, 0–2, default 0.7
top_pfloatNucleus sampling, 0–1, default 0.9
max_tokensintMaximum output tokens
streamboolWhether to stream the response, default false
toolsarrayTool definitions for function calling
tool_choicestringTool choice policy: auto / none / a named function