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GPT-5 nano vs Qwen2.5-Coder 32B Instruct
Comprehensive side-by-side LLM comparison
GPT-5 nano offers 272.0K more tokens in context window than Qwen2.5-Coder 32B Instruct. Both models have similar pricing. GPT-5 nano supports multimodal inputs. Qwen2.5-Coder 32B Instruct is available on 4 providers. Both models have their strengths depending on your specific coding needs.
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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
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.
10 months newer
Qwen2.5-Coder 32B Instruct
Alibaba Cloud / Qwen Team
2024-09-19
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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Qwen2.5-Coder 32B Instruct
Input:$0.09
Output:$0.09($0.27 cheaper)
Performance Metrics
Context window and performance specifications
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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:0.0%
Providers:2
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Qwen2.5-Coder 32B Instruct
Avg Score:0.0%
Providers:4