Moonshot AI (Kimi)kimi-k2.5VSOpenAIGPT-5 mini
Our Take
We recommend kimi-k2.5 for its clear benchmark advantage, or the 1.7x cheaper GPT-5 mini only if your budget requires optimizing costs for very high-volume pipelines. While kimi-k2.5 offers superior reasoning and coding, it carries a moderate price premium. Choose kimi-k2.5 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-k2.5 scored 50.7%, while GPT-5 mini scored 45.7%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. kimi-k2.5 scored 87.6%, while GPT-5 mini scored 81.6%.
Cost Efficiency: GPT-5 mini pricing ($0.25/M input, $2/M output) is 1.7x cheaper than kimi-k2.5 ($0.6/M input, $3/M output).
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Benchmarks & Scores
Coding (swe-bench-pro)Winner (+5.0%)
50.7%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+6.0%)
87.6%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$1.20Input: $0.60 | Output: $3.00Context 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)1.7x cheaper
$0.69Input: $0.25 | Output: $2.00Context WindowLarger
400k tokensFrequently Asked Questions about kimi-k2.5 vs GPT-5 mini
GPT-5 mini is cheaper than kimi-k2.5. GPT-5 mini has a blended cost of $0.69/1M tokens, which is about 1.7x cheaper than kimi-k2.5 at $1.20/1M tokens.
kimi-k2.5 is better for coding tasks on this benchmark. It scores 50.7% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning) compared to GPT-5 mini which scores 45.7%.
Related Matchups
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