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GPT-5 nano vs QwQ-32B-Preview
Comprehensive side-by-side LLM comparison
GPT-5 nano leads with 6.0% higher average benchmark score. GPT-5 nano offers 462.5K more tokens in context window than QwQ-32B-Preview. Both models have similar pricing. GPT-5 nano supports multimodal inputs. QwQ-32B-Preview is available on 4 providers. Overall, GPT-5 nano is the stronger choice for coding tasks.
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OpenAI
GPT-5 Nano was developed as the most compact variant in the GPT-5 family, designed for deployment in resource-constrained environments and edge computing scenarios. Built to bring next-generation AI capabilities to devices and applications where latency and efficiency are paramount, it distills GPT-5 innovations into a minimal footprint.
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Alibaba Cloud / Qwen Team
QwQ 32B Preview was introduced as an early access version of the QwQ reasoning model, designed to allow researchers and developers to experiment with advanced analytical capabilities. Built to gather feedback on reasoning-enhanced architecture, it represents an experimental step toward more thoughtful language models.
8 months newer
QwQ-32B-Preview
Alibaba Cloud / Qwen Team
2024-11-28
GPT-5 nano
OpenAI
2025-08-07
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Pricing Comparison
Cost per million tokens (USD)
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GPT-5 nano
Input:$0.05
Output:$0.40
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QwQ-32B-Preview
Input:$0.15
Output:$0.20($0.10 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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GPT-5 nano
Average Score:71.2%(+6.0%)
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QwQ-32B-Preview
Average Score:65.2%
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Knowledge Cutoff
Training data recency comparison
GPT-5 nano
2024-05-30
QwQ-32B-Preview
2024-11-28
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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GPT-5 nano
2 providers
OpenAI
Throughput: 500 tok/s
Latency: 0.3ms
ZeroEval
Throughput: 500 tok/s
Latency: 0.3ms
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GPT-5 nano
Avg Score:71.2%(+6.0%)
Providers:2
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QwQ-32B-Preview
Avg Score:65.2%
Providers:4