Alibaba Cloud (Qwen)Qwen3.6-27BVSOpenAIGPT-5.4 nano
Our Take
We recommend Qwen3.6-27B over GPT-5.4 nano because it holds a clear reasoning lead. Choose Qwen3.6-27B for offline data control and complex codebases, multi-file repositories, and architectural planning, or GPT-5.4 nano only if you prefer using a cloud-hosted API setup for complex codebases, multi-file repositories, and architectural planning.
▶WHY?
Benchmark Calculations & Evidence:
Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. Qwen3.6-27B scored 87.8%, while GPT-5.4 nano scored 82.8% (+5.0% gap).
Coding Performance: Both models were evaluated on the SWE-bench Pro benchmark. GPT-5.4 nano scored 52.4%, while Qwen3.6-27B scored 53.5% (+-1.1% gap).
Hosting Model: Qwen3.6-27B runs locally for $0 API costs, while GPT-5.4 nano is hosted via a cloud-hosted API setup.
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Benchmarks & Scores
Coding (swe-bench-pro)Winner (+1.1%)
53.5%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+5.0%)
87.8%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
Self HostLocal execution (zero API fees)Context Window
262.14k 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)
$0.46Input: $0.20 | Output: $1.25Context WindowLarger
400k tokensFrequently Asked Questions about Qwen3.6-27B vs GPT-5.4 nano
Qwen3.6-27B is better for coding tasks on this benchmark. It scores 53.5% 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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