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GPT-4.1 nano vs Qwen3-235B-A22B-Thinking-2507
Comprehensive side-by-side LLM comparison
Qwen3-235B-A22B-Thinking-2507 leads with 28.9% higher average benchmark score. GPT-4.1 nano offers 693.3K more tokens in context window than Qwen3-235B-A22B-Thinking-2507. GPT-4.1 nano is $2.80 cheaper per million tokens. GPT-4.1 nano supports multimodal inputs. Overall, Qwen3-235B-A22B-Thinking-2507 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 235B Thinking was developed as a reasoning-enhanced variant, designed to incorporate extended thinking capabilities into the large-scale Qwen3 architecture. Built to combine deliberate analytical processing with mixture-of-experts efficiency, it serves tasks requiring both deep reasoning and computational practicality.
3 months newer
GPT-4.1 nano
OpenAI
2025-04-14
Qwen3-235B-A22B-Thinking-2507
Alibaba Cloud / Qwen Team
2025-07-25
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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($2.80 cheaper)
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Qwen3-235B-A22B-Thinking-2507
Input:$0.30
Output:$3.00
Performance Metrics
Context window and performance specifications
Average performance across 5 common benchmarks
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GPT-4.1 nano
Average Score:43.7%
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Qwen3-235B-A22B-Thinking-2507
Average Score:72.7%(+28.9%)
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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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Qwen3-235B-A22B-Thinking-2507
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GPT-4.1 nano
Avg Score:43.7%
Providers:1
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Qwen3-235B-A22B-Thinking-2507
Avg Score:72.7%(+28.9%)
Providers:1