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ReasoningOpen SourceAlibaba
QwQ 32B
QwQ 32B is Alibaba's open-source reasoning model with a 32K token context window, designed for complex problem-solving and analytical tasks.
Context 32K
Tier Reasoning
Tools Supported
License Open Source
Input from
$1.20 / 1M tokens
across 1 provider
API Pricing
| Provider | Input / 1M | Output / 1M |
|---|---|---|
| $1.20 | $1.20 |
Prices updated daily. Last check: Sep 6, 2026
QwQ 32B pricing by provider
Input, output, and batch rates, plus alternatives, for one provider at a time.
Performance & Benchmarks
Source: Artificial Analysis →Intelligence
7.5 / 100
Math
29.0 / 100
Reasoning & Knowledge
- MMLU-Pro76.4%
- GPQA Diamond59.3%
- Humanity's Last Exam7.3%
Coding
- LiveCodeBench63.1%
Math
- AIME 202529.0%
- AIME78.0%
- MATH-50095.7%
Instruction & Long Context
- IFBench38.8%
- Long-Context Reasoning26.7%
Benchmarks measured Sep 2026. Scores are independent evaluations, not vendor-reported.
Model Details
General
- Creator
- Alibaba
- Family
- QwQ
- Tier
- Reasoning
- Context Window
- 32K
- Modalities
- Text
Capabilities
- Tool Calling
- Yes
- Open Source
- Yes
- Subtypes
- Chat Completion
- Aliases
- qwq-32b
Strengths & Limitations
Strengths
- Open-source model with full transparency and customization capabilities
- Specialized reasoning architecture optimized for analytical and problem-solving tasks
- 32K token context window for processing substantial amounts of information
- Tool calling support enables integration with external systems and APIs
- Output speed of 32.81 tokens per second provides responsive interactions
- No vendor lock-in or usage restrictions typical of proprietary models
- Can be deployed on-premises for data privacy and compliance requirements
Limitations
- Text-only input support - no image, audio, or video processing capabilities
- 32K context window is smaller than frontier models with 200K+ contexts
- Reasoning specialization may limit performance on general conversational tasks
- Requires technical expertise to deploy and maintain compared to API-based models
- Time-to-first-token of 446ms is slower than some optimized inference services
Key Features
•32K token context window
•Tool calling with external API integration
•Open-source model weights and architecture
•Text-based chat completion interface
•Reasoning-optimized neural architecture
•Self-hostable deployment options
•Streaming response generation
•Custom fine-tuning capabilities
About QwQ 32B
QwQ 32B is Alibaba's reasoning-focused language model within the QwQ family, positioned as a specialized model for complex analytical and problem-solving tasks. As an open-source model, it provides transparency and customization options not available with proprietary alternatives. The model features a 32,000 token context window and supports text-based interactions through chat completion interfaces.
The model is built specifically for reasoning tasks, offering capabilities in logical analysis, mathematical problem-solving, and structured thinking processes. It supports tool calling functionality, enabling integration with external systems and APIs. Performance benchmarks show an output speed of 32.81 tokens per second with a time-to-first-token of 446 milliseconds, indicating responsive real-time interaction capabilities.
QwQ 32B serves applications requiring deep analytical thinking rather than general conversational AI. Its open-source nature makes it suitable for organizations needing model transparency, custom fine-tuning, or on-premises deployment while maintaining reasoning capabilities.
Common Use Cases
QwQ 32B is designed for applications requiring structured reasoning and analytical problem-solving capabilities. Its reasoning specialization makes it well-suited for mathematical computations, logical analysis, research assistance, and complex decision-making processes. The open-source nature enables organizations to deploy it for sensitive analytical workloads where data privacy is critical, such as financial modeling, scientific research, or proprietary business analysis. The tool calling functionality supports integration into analytical workflows and automated reasoning systems. However, its reasoning focus makes it less optimal for general conversational AI, creative writing, or customer service applications where broader language capabilities are more important than deep analytical thinking.
Frequently Asked Questions
How much does QwQ 32B cost per million tokens?
QwQ 32B pricing varies significantly by provider and deployment method. As an open-source model, you can also self-host it without per-token charges. Check the pricing table above for current rates across different inference providers.
What is QwQ 32B best used for?
QwQ 32B excels at reasoning-intensive tasks including mathematical problem-solving, logical analysis, research assistance, and structured decision-making. Its specialized reasoning architecture makes it particularly effective for analytical workloads requiring step-by-step thinking and complex problem decomposition.
Can I run QwQ 32B on my own infrastructure?
Yes, QwQ 32B is open-source, meaning you can download the model weights and run it on your own hardware. This enables on-premises deployment for data privacy, custom fine-tuning, and avoiding per-token usage costs, though it requires technical expertise to set up and maintain.