QwQ-32B
About QwQ-32B
QwQ is the reasoning model of the Qwen series. Compared with conventional instruction-tuned models, QwQ, which is capable of thinking and reasoning, can achieve significantly enhanced performance in downstream tasks, especially hard problems. QwQ-32B is the medium-sized reasoning model, which is capable of achieving competitive performance against state-of-the-art reasoning models, e.g., DeepSeek-R1, o1-mini. The model incorporates technologies like RoPE, SwiGLU, RMSNorm, and Attention QKV bias, with 64 layers and 40 Q attention heads (8 for KV in GQA architecture)
Available Serverless
Run queries immediately, pay only for usage
$
0.15
/
$
0.58
Per 1M Tokens (input/output)
Metadata
Specification
State
Available
Architecture
Calibrated
No
Mixture of Experts
No
Total Parameters
32B
Activated Parameters
32.5B
Reasoning
No
Precision
FP8
Context length
131K
Max Tokens
131K
Supported Functionality
Serverless
Supported
Serverless LoRA
Not supported
Fine-tuning
Not supported
Embeddings
Not supported
Rerankers
Not supported
Support image input
Not supported
JSON Mode
Not supported
Structured Outputs
Not supported
Tools
Supported
Fim Completion
Not supported
Chat Prefix Completion
Not supported
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Total Context:
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Input:
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Max output:
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Release on: Oct 15, 2025
Total Context:
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Max output:
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Input:
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Release on: Oct 4, 2025
Total Context:
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Max output:
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Input:
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Release on: Oct 4, 2025
Total Context:
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Max output:
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Input:
$
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Release on: Oct 5, 2025
Total Context:
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Max output:
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Input:
$
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Output:
$
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Max output:
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Input:
$
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Output:
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/ M Tokens
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Model FAQs: Usage, Deployment
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