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Z.ai: GLM 4.7Code Agents, Think Deep

Try Z.ai: GLM 4.7API Documentation

Reason. Code. Deploy.

Agentic Coding

SWE-bench 73.8%

Leads open-source models on verified coding benchmarks with stable multi-step reasoning.

Thinking Modes

Interleaved Preserved

Thinks before actions, retains context across turns for complex agent workflows.

Context Power

200K Tokens

Handles long inputs with 128K output via Z.ai: GLM 4.7 API.

Examples

See what Z.ai: GLM 4.7 can create

Copy any prompt below and try it yourself in the playground.

UI Component

“Generate a modern React component for a responsive dashboard with dark mode toggle, charts using Recharts, and clean Tailwind CSS styling. Include full code with imports.”

Agent Workflow

“Design a Python agent that uses interleaved thinking to scrape a webpage, extract product data, analyze prices with pandas, and output a CSV summary. Enable preserved thinking mode.”

Math Proof

“Prove the fundamental theorem of calculus step-by-step using turn-level thinking. Explain integrals and derivatives with formal notation and examples.”

Terminal Script

“Write a bash script for terminal automation: monitor logs, alert on errors via email, and summarize trends. Optimize for efficiency on Linux systems.”

For Developers

A few lines of code.
Agents live. One call.

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

  • Serverless: scales to zero, scales to millions
  • Pay per token, no minimums
  • Python and JavaScript SDKs, plus REST API
API Documentation 
import requests


response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

FAQ

Common questions about Z.ai: GLM 4.7

Read the docs

Z.ai: GLM 4.7 is a 358B parameter MoE LLM optimized for agentic coding and reasoning. It tops SWE-bench at 73.8% and supports 200K context. Use via Z.ai: GLM 4.7 API.

OpenAI-compatible chat completions endpoint accepts messages array. Set model to zai-org/GLM-4.7 with bearer token. Supports streaming and tool calling.

Advanced thinking modes like interleaved and preserved improve multi-turn stability over predecessors. Excels in UI generation and terminal tasks. MIT licensed open weights.

200K input tokens with 128K max output. Handles long conversations and agent workflows without truncation. Ideal for complex reasoning.

73.8% SWE-bench Verified, 87.4% τ²-Bench, 52% BrowseComp. Outperforms GLM-4.6 in coding and tool use. Strong multilingual support.

Built for task-oriented development with preserved thinking across turns. Generates clean code, modern UIs, and stable reasoning traces. Deploy via API instantly.

Ready to create?

Start generating with Z.ai: GLM 4.7 on ModelsLab.

Try Z.ai: GLM 4.7API Documentation