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GPT-5 nano vs Qwen3 32B
Comprehensive side-by-side LLM comparison
GPT-5 nano leads with 12.3% higher average benchmark score. GPT-5 nano offers 272.0K more tokens in context window than Qwen3 32B. Both models have similar pricing. GPT-5 nano supports multimodal inputs. 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
Qwen3 32B was developed as a dense 32-billion-parameter model in the Qwen3 family, designed to provide strong language understanding without mixture-of-experts complexity. Built for applications requiring straightforward deployment and reliable performance, it serves as a capable mid-to-large-scale foundation model.
3 months newer
Qwen3 32B
Alibaba Cloud / Qwen Team
2025-04-29
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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Qwen3 32B
Input:$0.10
Output:$0.30($0.05 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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GPT-5 nano
Average Score:85.2%(+12.3%)
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Qwen3 32B
Average Score:72.9%
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Knowledge Cutoff
Training data recency comparison
GPT-5 nano
2024-05-30
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:85.2%(+12.3%)
Providers:2
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Qwen3 32B
Avg Score:72.9%
Providers:3