QwQ-32B API

Reasoning with reinforcement learning.
Output

Overview

QwQ-32B Description

QwQ-32B is a compact yet powerful 32-billion-parameter language model optimized for advanced reasoning, coding, and structured problem-solving. Combining reinforcement learning and agentic reasoning capabilities, it delivers performance comparable to models with significantly larger parameter counts. QwQ-32B supports extended context windows up to 131K tokens, enabling effective handling of complex, long-form workflows. Its efficiency and adaptability make it ideal for dynamic AI agents and specialized reasoning tasks.

Technical Specifications

  • Model Size: 32.5 billion parameters (31B non-embedding)
  • Layers: 64 transformer layers
  • Context Window: 131,072 tokens
  • Architecture: Transformer with RoPE positional encoding, SwiGLU activations, RMSNorm, and QKV attention biasing
  • Training: Combination of pretraining, supervised fine-tuning, and multi-stage reinforcement learning
  • Alignment: Uses RL-based methods to improve response correctness and reduce bias, especially in math and coding domains

Performance Highlights

  • Achieves near-parity with much larger models (e.g., DeepSeek-R1 671B) on complex reasoning and coding benchmarks
  • Excels in mathematical problem solving, logical workflows, and adaptive agentic reasoning
  • Robust handling of long documents and context-rich tasks through an exceptionally wide context window

Key Capabilities

  • Reinforcement Learning Enhanced Reasoning: Employs multi-stage RL for adaptive problem-solving
  • Agentic Reasoning: Dynamically adjusts reasoning strategies based on input context and feedback
  • Extended Context Handling: Supports very long-form inputs for complex document analysis and dialogue
  • Efficient Coding Assistance: Strong performance in code generation and debugging across multiple languages

Optimal Use Cases

  • Scientific and mathematical research requiring deep structured reasoning
  • Complex software development, debugging, and code synthesis
  • Financial and engineering logical workflows
  • AI-powered agents needing flexible reasoning and adaptability
Code Samples:

The model is available on the AI/ML API platform as "QwQ-32B" .

API Documentation:

Detailed API Documentation is available here.

Ethical Guidelines

The Qwen Team has emphasized safety by employing rule-based verifiers during training to ensure correctness in outputs for math and coding tasks. However, users should remain cautious about potential biases or inaccuracies in less-tested domains.

Licensing

QwQ-32B is open-source under the Apache 2.0 license, allowing free use for commercial and research purposes. It is deployable on consumer-grade hardware due to its compact size.

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Get QwQ-32B API here.

Use cases

  • Research in AI reasoning and problem-solving
  • Complex scientific and mathematical application support
  • Programming assistant and code generation tools
  • Conversational agents requiring long context understanding
  • AI-assisted workflows and automation in technical domains
  • Educational and tutoring systems for STEM subjects

How to use QwQ-32B API

Install any OpenAI-compatible SDK, point it at api.aimlapi.com/v1, and set the model to .

OpenAI-compatible — swap the base URL and it works with your existing SDK.

QwQ-32B API Pricing

TypePrice
Input
Output

QwQ-32B Benchmarks

BenchmarkScoreWhat it measuresSourceRetrieved
Intelligence
9.5
Composite score across standardised reasoning, knowledge and problem-solving evaluations, measured independently by Artificial AnalysisSourceSeptember 12, 2026
Math
29
Composite score across standardised mathematics evaluations, measured independently by Artificial AnalysisSourceSeptember 12, 2026

QwQ-32B vs other models

ModelInputOutputContextBest for
QwQ-32B
This page
$6.5 / 1M tokens
$39 / 1M tokens
1M tokens
Reasoning + agents
$2.6 / 1M tokens
$13 / 1M tokens
1M tokens
Balanced coding + agents
$3.9 / 1M tokens
$19.5 / 1M tokens
1M tokens
Long-context, multimodal & agentic workflows
$1.95 / 1M tokens
$11.7 / 1M tokens
1M tokens
Reasoning + agents

Frequently asked questions

Yes, QwQ-32B can stream responses as they are generated.

Yes, QwQ-32B supports both function calling and structured outputs.

QwQ-32B was built by Alibaba Cloud.

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