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AnthropicClaude Opus 4.7VSMoonshot AI (Kimi)kimi-k2.5

Analysis by:the whichllmmodel Editorial Team|Updated: June 2026

Our Take

We recommend Claude Opus 4.7 if you need peak intelligence for reasoning and coding tasks, or the 8.3x cheaper kimi-k2.5 to optimize your budget for high-volume pipelines. While Claude Opus 4.7 holds a clear performance lead, it carries a heavy price premium. Choose Claude Opus 4.7 for complex logic, or kimi-k2.5 for budget efficiency.
WHY?
Benchmark Calculations & Evidence:
  • Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. Claude Opus 4.7 scored 64.3%, while kimi-k2.5 scored 50.7%.
  • Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. Claude Opus 4.7 scored 94.2%, while kimi-k2.5 scored 87.6%.
  • Cost Efficiency: kimi-k2.5 pricing ($0.6/M input, $3/M output) is 8.3x cheaper than Claude Opus 4.7 ($5/M input, $25/M output).
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    Model Specs

    Claude Opus 4.7

    Benchmarks & Scores

    Coding (swe-bench-pro)Winner (+13.6%)
    64.3%

    complex codebases, multi-file repositories, and architectural planning

    Reasoning (gpqa-diamond)Winner (+6.6%)
    94.2%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)
    $10.00Input: $5.00 | Output: $25.00
    Context WindowLarger
    1.05M tokens
    Model Specs

    kimi-k2.5

    Open SourceAPI Available

    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)8.3x cheaper
    $1.20Input: $0.60 | Output: $3.00
    Context Window
    262.14k tokens

    Frequently Asked Questions about Claude Opus 4.7 vs kimi-k2.5

    kimi-k2.5 is cheaper than Claude Opus 4.7. kimi-k2.5 has a blended cost of $1.20/1M tokens, which is about 8.3x cheaper than Claude Opus 4.7 at $10.00/1M tokens.

    Claude Opus 4.7 is better for coding tasks on this benchmark. It scores 64.3% 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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