Moonshot AI (Kimi)kimi-k2.5VSMoonshot AI (Kimi)kimi-k2.6
Our Take
We recommend kimi-k2.6 for its clear benchmark advantage, or the 1.4x cheaper kimi-k2.5 only if your budget requires optimizing costs for very high-volume pipelines. While kimi-k2.6 offers superior reasoning and coding, it carries a moderate price premium. Choose kimi-k2.6 for quality, or kimi-k2.5 for cost optimization.
▶WHY?
Benchmark Calculations & Evidence:
Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. kimi-k2.6 scored 58.6%, while kimi-k2.5 scored 50.7%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. kimi-k2.6 scored 90.5%, while kimi-k2.5 scored 87.6%.
Cost Efficiency: kimi-k2.5 pricing ($0.6/M input, $3/M output) is 1.4x cheaper than kimi-k2.6 ($0.95/M input, $4/M output).
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Benchmarks & Scores
Coding (swe-bench-pro)
50.7%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
87.6%graduate-level science QA
Cost & Context
Cost (per 1M tokens)1.4x cheaper
$1.20Input: $0.60 | Output: $3.00Context Window
262.14k tokensBenchmarks & Scores
Coding (swe-bench-pro)Winner (+7.9%)
58.6%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+2.9%)
90.5%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$1.71Input: $0.95 | Output: $4.00Context Window
262.14k tokensFrequently Asked Questions about kimi-k2.5 vs kimi-k2.6
kimi-k2.5 is cheaper than kimi-k2.6. kimi-k2.5 has a blended cost of $1.20/1M tokens, which is about 1.4x cheaper than kimi-k2.6 at $1.71/1M tokens.
kimi-k2.6 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 kimi-k2.5 which scores 50.7%.
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