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GPT-4.1 nano vs Qwen3 32B
Comprehensive side-by-side LLM comparison
Qwen3 32B leads with 52.0% higher average benchmark score. GPT-4.1 nano offers 824.3K more tokens in context window than Qwen3 32B. Both models have similar pricing. GPT-4.1 nano supports multimodal inputs. Qwen3 32B is available on 3 providers. Overall, Qwen3 32B is the stronger choice for coding tasks.
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OpenAI
GPT-4.1 Nano was developed as the smallest and most efficient variant in the GPT-4.1 family, designed for applications requiring minimal latency and resource usage. Built to enable AI capabilities on edge devices and resource-constrained environments, it distills GPT-4.1 capabilities into an ultra-compact form factor.
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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.
15 days newer
GPT-4.1 nano
OpenAI
2025-04-14
Qwen3 32B
Alibaba Cloud / Qwen Team
2025-04-29
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Pricing Comparison
Cost per million tokens (USD)
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GPT-4.1 nano
Input:$0.10
Output:$0.40
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Qwen3 32B
Input:$0.10
Output:$0.30($0.10 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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GPT-4.1 nano
Average Score:29.4%
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Qwen3 32B
Average Score:81.4%(+52.0%)
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Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
2024-05-31
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-4.1 nano
1 providers
OpenAI
Throughput: 200 tok/s
Latency: 2ms
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Qwen3 32B
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GPT-4.1 nano
Avg Score:29.4%
Providers:1
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Qwen3 32B
Avg Score:81.4%(+52.0%)
Providers:3