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GPT-4.1 nano vs Qwen2.5-Coder 32B Instruct
Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 5.0% higher average benchmark score. GPT-4.1 nano offers 824.3K more tokens in context window than Qwen2.5-Coder 32B Instruct. Both models have similar pricing. GPT-4.1 nano supports multimodal inputs. Qwen2.5-Coder 32B Instruct is available on 4 providers. Overall, GPT-4.1 nano 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
Qwen 2.5 Coder 32B was developed as a specialized coding model, designed to excel at programming tasks with 32 billion parameters specifically optimized for code. Built to understand and generate code across multiple programming languages, it serves developers requiring advanced code completion, debugging, and explanation capabilities.
6 months newer
Qwen2.5-Coder 32B Instruct
Alibaba Cloud / Qwen Team
2024-09-19
GPT-4.1 nano
OpenAI
2025-04-14
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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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Qwen2.5-Coder 32B Instruct
Input:$0.09
Output:$0.09($0.32 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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GPT-4.1 nano
Average Score:80.1%(+5.0%)
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Qwen2.5-Coder 32B Instruct
Average Score:75.1%
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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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Qwen2.5-Coder 32B Instruct
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GPT-4.1 nano
Avg Score:80.1%(+5.0%)
Providers:1
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Qwen2.5-Coder 32B Instruct
Avg Score:75.1%
Providers:4