---
title: Qwen QwQ-32B — Reasoning LLM | ModelsLab
description: Access Qwen QwQ-32B API for advanced reasoning in math, coding, and logic. Generate precise solutions via OpenAI-compatible endpoints. Try now.
url: https://modelslab-frontend-v2-927501783998.us-east4.run.app/qwen-qwq-32b
canonical: https://modelslab-frontend-v2-927501783998.us-east4.run.app/qwen-qwq-32b
type: website
component: Seo/ModelPage
generated_at: 2026-05-13T09:44:00.055431Z
---

Available now on ModelsLab · Language Model

Qwen QwQ-32B
Reason Deeper. Solve Harder
---

[Try Qwen QwQ-32B](/models/qwen/Qwen-QwQ-32B) [API Documentation](https://docs.modelslab.com)

Master Complex Reasoning
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Math Mastery

### AIME24 79.5 Score

Outperforms o1-mini on multi-step math problems with chain-of-thought reasoning.

Code Precision

### Algorithm Optimization

Generates, debugs, and integrates code rivaling DeepSeek-R1 performance.

API Ready

### 131K Context Window

Handles long prompts via Qwen QwQ-32B API for comprehensive problem solving.

Examples

See what Qwen QwQ-32B can create
---

Copy any prompt below and try it yourself in the [playground](/models/qwen/Qwen-QwQ-32B).

Math Proof

“Prove the Pythagorean theorem using step-by-step reasoning, including geometric visualization and algebraic verification. Output final proof in LaTeX.”

Code Debug

“Debug this Python function for sorting linked lists: def merge\_sort(head): ... Identify errors and provide corrected implementation with time complexity analysis.”

Logic Puzzle

“Solve Einstein's riddle: five houses, colors, nationalities, drinks, smokes, pets. Who owns the fish? Reason step-by-step without assumptions.”

Research Summary

“Analyze quantum entanglement experiments from 2020-2025. Summarize key findings, implications for computing, and unresolved challenges.”

For Developers

A few lines of code.
Reasoning API. 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 ](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 Qwen QwQ-32B
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[Read the docs ](https://docs.modelslab.com)

### What is Qwen QwQ-32B?

Qwen QwQ-32B is a 32B parameter reasoning model from Qwen series. It excels in math, coding, and logic via reinforcement learning. Competes with DeepSeek-R1 and o1-mini.

### How to use Qwen QwQ-32B API?

Call via OpenAI-compatible /chat/completions endpoint with model="Qwen/QwQ-32B". Supports streaming and 131K context. Use temperature=0.6 for best results.

### What are Qwen QwQ-32B benchmarks?

AIME24: 79.5, BFCL: 66.4, LiveBench: 73.1. Beats o1-mini on math, DeepSeek-R1 on coding tasks. Full 128K context available.

### Is Qwen QwQ-32B a good alternative?

Qwen QwQ-32B alternative matches SOTA models at lower cost. Ideal for reasoning-heavy apps. Deploy via DeepInfra, Groq, or OpenRouter.

### Qwen QwQ-32B model use cases?

Math proofs, code generation, algorithm debugging, research analysis. Handles complex multi-step reasoning. Supports guided JSON output.

### Qwen QwQ-32B vs instruction models?

QwQ-32B uses thinking steps for hard problems, outperforming tuned models. Enable reasoning_format=parsed for clean output.

Ready to create?
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Start generating with Qwen QwQ-32B on ModelsLab.

[Try Qwen QwQ-32B](/models/qwen/Qwen-QwQ-32B) [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*