whichLlmmodel
Back to Dashboard

GoogleGemini 2.5 ProVSMoonshot AI (Kimi)kimi-k2.6

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

Our Take

We recommend kimi-k2.6 for superior overall value and reasoning capabilities, as it is cheaper or equal in cost while delivering peak intelligence. While kimi-k2.6 excels at complex complex codebases, multi-file repositories, and architectural planning, Gemini 2.5 Pro is suited for scripting multi-file code and clearly defined tasks. Choose kimi-k2.6 for architectural codebase planning, or Gemini 2.5 Pro if you specifically require its simpler functions profile.
WHY?
Benchmark Calculations & Evidence:
  • Coding Evaluation: Gemini 2.5 Pro was evaluated on SWE-bench Verified (scoring 59.6%), while kimi-k2.6 was evaluated on SWE-bench Pro (scoring 58.6%).
  • Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. kimi-k2.6 scored 90.5%, while Gemini 2.5 Pro scored 84.4%.
  • Cost Efficiency: Gemini 2.5 Pro pricing ($1.25/M input, $10/M output) is 0.5x cheaper than kimi-k2.6 ($0.95/M input, $4/M output).
  • Was this recommendation helpful?
    Model Specs

    Gemini 2.5 Pro

    Benchmarks & Scores

    Coding (swe-bench-verified)
    59.6%

    multi-file code and clearly defined tasks

    Reasoning (gpqa-diamond)
    84.4%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)
    $3.44Input: $1.25 | Output: $10.00
    Context WindowLarger
    1.05M tokens
    Model Specs

    kimi-k2.6

    Open SourceAPI Available

    Benchmarks & Scores

    Coding (swe-bench-pro)
    58.6%

    complex codebases, multi-file repositories, and architectural planning

    Reasoning (gpqa-diamond)Winner (+6.1%)
    90.5%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)2.0x cheaper
    $1.71Input: $0.95 | Output: $4.00
    Context Window
    262.14k tokens

    Frequently Asked Questions about Gemini 2.5 Pro vs kimi-k2.6

    kimi-k2.6 is cheaper than Gemini 2.5 Pro. kimi-k2.6 has a blended cost of $1.71/1M tokens, which is about 2.0x cheaper than Gemini 2.5 Pro at $3.44/1M tokens.

    For coding tasks, Gemini 2.5 Pro scores 59.6% on swe-bench-verified (multi-file code and clearly defined tasks), while kimi-k2.6 scores 58.6% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning).

    Do you want to find a model for your constraints?

    Use our interactive model finder to filter LLMs by reasoning capability, coding performance, cost, and context length.

    Open Model Finder