---
title: Z.ai: GLM 4.5 Air — Reasoning LLM | ModelsLab
description: Access Z.ai: GLM 4.5 Air for agentic reasoning and coding via API. Deploy 106B MoE model with 131K context. Try hybrid thinking mode now.
url: https://modelslab-frontend-v2-927501783998.us-east4.run.app/zai-glm-45-air
canonical: https://modelslab-frontend-v2-927501783998.us-east4.run.app/zai-glm-45-air
type: website
component: Seo/ModelPage
generated_at: 2026-05-13T10:35:11.124531Z
---

Available now on ModelsLab · Language Model

Z.ai: GLM 4.5 Air
Reason. Code. Act.
---

[Try Z.ai: GLM 4.5 Air](/models/open_router/z-ai-glm-4.5-air) [API Documentation](https://docs.modelslab.com)

Build Agents Fast.
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Hybrid Reasoning

### Thinking Mode On

Toggle reasoning for math, science, logic via enabled boolean in Z.ai: GLM 4.5 Air API.

MoE Efficiency

### 106B Compact Power

12B active parameters deliver agentic tasks in z ai glm 4.5 air model with low latency.

Long Context

### 131K Token Window

Handle complex chains in Z.ai: GLM 4.5 Air alternative to heavy frontier LLMs.

Examples

See what Z.ai: GLM 4.5 Air can create
---

Copy any prompt below and try it yourself in the [playground](/models/open_router/z-ai-glm-4.5-air).

Math Proof

“Prove Fermat's Last Theorem step-by-step using thinking mode. Explain each algebraic manipulation and reference key historical context.”

Code Debugger

“Analyze this Python function for bugs: def factorial(n): if n == 0: return 1 else: return n \* factorial(n-1). Fix recursion error and optimize for large n.”

Logic Puzzle

“Solve: Three houses in a row, owners A B C drink water milk tea, own cat dog bird. Clues: Brit in red house, etc. Output grid solution.”

Agent Plan

“Plan multi-step task: Research API endpoints, write integration code, test with sample data. Use tools if needed in thinking mode.”

For Developers

A few lines of code.
Agents. One Call.
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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 ](https://docs.modelslab.com)

PythonJavaScriptcURL

Copy

```
<code>import requests

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

FAQ

Common questions about Z.ai: GLM 4.5 Air
---

[Read the docs ](https://docs.modelslab.com)

### What is Z.ai: GLM 4.5 Air?

Z.ai: GLM 4.5 Air is a 106B MoE LLM with 12B active parameters for reasoning and agents. It ranks 6th on 12 benchmarks. Supports 131K context.

### How does z ai glm 4.5 air API work?

Call via OpenAI-compatible endpoint with reasoning: enabled boolean. Use thinking mode for complex tasks. Available on Z.ai, OpenRouter.

### What are Z.ai: GLM 4.5 Air model strengths?

Excels in coding, agentic tasks, math reasoning. Hybrid modes balance speed and depth. Competitive at lower cost than flagships.

### Is Z.ai: GLM 4.5 Air alternative to GPT?

Yes, z.ai: glm 4.5 air offers similar agentic performance with efficiency. Open-weights on HuggingFace. Ranks near top models.

### Z.ai: GLM 4.5 Air LLM context length?

131,072 tokens input, up to 98K output. Handles long agent chains. Matches larger GLM-4.5 capabilities.

### Pricing for Z.ai: GLM 4.5 Air API?

Around $0.13/M input, $0.85/M output tokens via providers. Low latency at 357ms TTFT, 48 tok/s throughput.

Ready to create?
---

Start generating with Z.ai: GLM 4.5 Air on ModelsLab.

[Try Z.ai: GLM 4.5 Air](/models/open_router/z-ai-glm-4.5-air) [API Documentation](https://docs.modelslab.com)

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*This markdown version is optimized for AI agents and LLMs.*

**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)

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*Generated by ModelsLab - 2026-05-13*