Alibaba Cloud (Qwen)Qwen3.7-MaxVSOpenAIGPT-5.4 nano
Our Take
We recommend Qwen3.7-Max if you need peak intelligence for reasoning and coding tasks, or the 8.1x cheaper GPT-5.4 nano to optimize your budget for high-volume pipelines. While Qwen3.7-Max holds a clear performance lead, it carries a heavy price premium. Choose Qwen3.7-Max for complex logic, or GPT-5.4 nano for budget efficiency.
▶WHY?
Benchmark Calculations & Evidence:
Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. Qwen3.7-Max scored 60.6%, while GPT-5.4 nano scored 52.4%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. Qwen3.7-Max scored 92.4%, while GPT-5.4 nano scored 82.8%.
Cost Efficiency: GPT-5.4 nano pricing ($0.2/M input, $1.25/M output) is 8.1x cheaper than Qwen3.7-Max ($2.5/M input, $7.5/M output).
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Benchmarks & Scores
Coding (swe-bench-pro)Winner (+8.2%)
60.6%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+9.6%)
92.4%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$3.75Input: $2.50 | Output: $7.50Context WindowLarger
1.05M tokensBenchmarks & Scores
Coding (swe-bench-pro)
52.4%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
82.8%graduate-level science QA
Cost & Context
Cost (per 1M tokens)8.1x cheaper
$0.46Input: $0.20 | Output: $1.25Context Window
400k tokensFrequently Asked Questions about Qwen3.7-Max vs GPT-5.4 nano
GPT-5.4 nano is cheaper than Qwen3.7-Max. GPT-5.4 nano has a blended cost of $0.46/1M tokens, which is about 8.1x cheaper than Qwen3.7-Max at $3.75/1M tokens.
Qwen3.7-Max is better for coding tasks on this benchmark. It scores 60.6% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning) compared to GPT-5.4 nano which scores 52.4%.
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