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GPT-4.1 nano vs Qwen2.5 72B Instruct
Comprehensive side-by-side LLM comparison
Qwen2.5 72B Instruct leads with 4.1% higher average benchmark score. GPT-4.1 nano offers 941.1K more tokens in context window than Qwen2.5 72B Instruct. Both models have similar pricing. GPT-4.1 nano supports multimodal inputs. Qwen2.5 72B Instruct is available on 4 providers. Both models have their strengths depending on your specific coding needs.
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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 72B was developed as the flagship text model in the Qwen 2.5 series, designed to provide advanced language capabilities with 72 billion parameters. Built to compete with frontier models in reasoning, coding, and general language tasks, it represents Qwen's most capable instruction-following model in this generation.
6 months newer
Qwen2.5 72B 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($0.25 cheaper)
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Qwen2.5 72B Instruct
Input:$0.35
Output:$0.40
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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GPT-4.1 nano
Average Score:62.4%
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Qwen2.5 72B Instruct
Average Score:66.5%(+4.1%)
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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 72B Instruct
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GPT-4.1 nano
Avg Score:62.4%
Providers:1
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Qwen2.5 72B Instruct
Avg Score:66.5%(+4.1%)
Providers:4