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Qwen QwQ-32BReason Deeper. Solve Harder

Try Qwen QwQ-32BAPI Documentation

Master Complex Reasoning

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.

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 
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 Qwen QwQ-32B

Read the docs

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.

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

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

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

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

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

Ready to create?

Start generating with Qwen QwQ-32B on ModelsLab.

Try Qwen QwQ-32BAPI Documentation