Alibaba Cloud (Qwen)Qwen3.6-27BVSOpenAIGPT-5.4 mini
Our Take
We recommend Qwen3.6-27B for zero-cost private inference on your own hardware, or GPT-5.4 mini if you need instant cloud scaling without managing compute. Choose Qwen3.6-27B for offline data control and complex codebases, multi-file repositories, and architectural planning, or GPT-5.4 mini for complex codebases, multi-file repositories, and architectural planning.
▶WHY?
Benchmark Calculations & Evidence:
Reasoning Accuracy: Qwen3.6-27B scores 87.8% on reasoning, while GPT-5.4 mini scores 87.5%.
Coding Performance: Both models were evaluated on the SWE-bench Pro benchmark. GPT-5.4 mini scored 54.4%, while Qwen3.6-27B scored 53.5% (+0.9% gap).
Context Window: GPT-5.4 mini supports 400k, while Qwen3.6-27B supports 262k.
Hosting Model: Qwen3.6-27B runs locally for $0 API costs, while GPT-5.4 mini is a cloud API.
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Benchmarks & Scores
Coding (swe-bench-pro)
53.5%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+0.3%)
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)Winner (+0.9%)
54.4%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
87.5%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$1.69Input: $0.75 | Output: $4.50Context WindowLarger
400k tokensFrequently Asked Questions about Qwen3.6-27B vs GPT-5.4 mini
GPT-5.4 mini is better for coding tasks on this benchmark. It scores 54.4% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning) compared to Qwen3.6-27B which scores 53.5%.
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