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.
GPQA Diamond
Graduate-level science questions written to resist web search.
LiveCodeBench
Competitive programming problems published after training cutoffs.
MMLU-Pro
Multiple-choice knowledge and reasoning across 14 subjects.
MATH-500
Competition mathematics problems.
QwQ-32B API pricing
| Usage | Price | Unit |
|---|---|---|
| Input | $1.26 | 1M tokens |
| Output | $1.26 | 1M 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.
| Model | Input | Output |
|---|---|---|
| $1.26 | $1.26 | |
| $0.15 | $0.47 | |
| $0.16 | $0.47 | |
| $0.4761 | $3.39 | |
| $4.23 | $12.7 |
Related articles
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.

