Moonshot AI (Kimi)Kimi K2.7 CodeVSOpenAIGPT-5 mini
Our Take
We recommend Kimi K2.7 Code for its clear benchmark advantage, or the 2.5x cheaper GPT-5 mini only if your budget requires optimizing costs for very high-volume pipelines. While Kimi K2.7 Code offers superior reasoning and coding, it carries a moderate price premium. Choose Kimi K2.7 Code for quality, or GPT-5 mini for cost optimization.
▶WHY?
Benchmark Calculations & Evidence:
Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. Kimi K2.7 Code scored 58.6%, while GPT-5 mini scored 45.7%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. Kimi K2.7 Code scored 90%, while GPT-5 mini scored 81.6%.
Cost Efficiency: GPT-5 mini pricing ($0.25/M input, $2/M output) is 2.5x cheaper than Kimi K2.7 Code ($0.95/M input, $4/M output).
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Benchmarks & Scores
Coding (swe-bench-pro)Winner (+12.9%)
58.6%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+8.4%)
90%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$1.71Input: $0.95 | Output: $4.00Context Window
262.14k tokensBenchmarks & Scores
Coding (swe-bench-pro)
45.7%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
81.6%graduate-level science QA
Cost & Context
Cost (per 1M tokens)2.5x cheaper
$0.69Input: $0.25 | Output: $2.00Context WindowLarger
400k tokensFrequently Asked Questions about Kimi K2.7 Code vs GPT-5 mini
GPT-5 mini is cheaper than Kimi K2.7 Code. GPT-5 mini has a blended cost of $0.69/1M tokens, which is about 2.5x cheaper than Kimi K2.7 Code at $1.71/1M tokens.
Kimi K2.7 Code is better for coding tasks on this benchmark. It scores 58.6% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning) compared to GPT-5 mini which scores 45.7%.
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