QwQ-32B API

Explore QwQ-32B: Alibaba's compact reasoning model delivering state-of-the-art performance in math, coding, and logical problem-solving tasks!

Modalities
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Model type
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QwQ-32B overview

QwQ-32B specs

Developer
Alibaba Cloud
Input
Text
Output
Text
API
OpenAI-compatible, base URL https://api.aimlapi.com/v1

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)
  • 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" .

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

Capabilities

  • Function calling
  • Streaming
  • Structured outputs

QwQ-32B benchmarks by Artificial Analysis

See how QwQ-32B scores on independent evaluations. Data retrieved Nov 3, 2026.

Benchmark results

Compare 18 models available on AI/ML API across 5 independent benchmarks.

Humanity's Last Exam

Expert-written questions across academic subjects.

QwQ-32B API pricing

QwQ-32B pricing in US dollars
UsagePriceUnit
Input$1.261M tokens
Output$1.261M tokens

QwQ-32B is unlisted on AI/ML API. The rates apply to existing integrations; the models below are current alternatives.

Prices from the AI/ML API price list, checked on Nov 4, 2026.

QwQ-32B vs other models: token prices

AI/ML API input and output rates for 5 models, per million tokens.

AI/ML API model prices in USD per million tokens
ModelInputOutput
QwQ-32B$1.26$1.26
Qwen3.8 Omni Flash$0.15$0.47
Qwen3.8-Flash$0.16$0.47
Qwen 3.8 27B$0.4761$3.39
Qwen3.8 Max Prime$4.23$12.7

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QwQ-32B FAQ

Does QwQ-32B support streaming?

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

Does QwQ-32B support tool calling and structured outputs?

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

Who created QwQ-32B?

QwQ-32B was built by Alibaba Cloud.

Start building with QwQ-32B