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Alibaba Cloud (Qwen)Qwen3.6-PlusVSMoonshot AI (Kimi)kimi-k2.5

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

Our Take

We recommend choosing Qwen3.6-Plus because it outperforms or matches kimi-k2.5 across reasoning, coding, and context capacity while being cheaper or equal in cost. Choose Qwen3.6-Plus for superior overall value.
▶WHY?
Benchmark Calculations & Evidence:
  • Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. Qwen3.6-Plus scored 56.6%, while kimi-k2.5 scored 50.7%.
  • Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. Qwen3.6-Plus scored 90.4%, while kimi-k2.5 scored 87.6%.
  • Context Window: Qwen3.6-Plus supports a 1M context window compared to 262k for kimi-k2.5.
  • Cost Comparison: Qwen3.6-Plus blended CPM is $0.5/$3 compared to $0.6/$3 for kimi-k2.5.
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    Model Specs

    Qwen3.6-Plus

    Website

    Benchmarks & Scores

    Coding (swe-bench-pro)Winner (+5.9%)
    56.6%

    complex codebases, multi-file repositories, and architectural planning

    Reasoning (gpqa-diamond)Winner (+2.8%)
    90.4%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)1.1x cheaper
    $1.13Input: $0.50 | Output: $3.00
    Context WindowLarger
    1.05M tokens
    Model Specs

    kimi-k2.5

    Open SourceAPI Available
    Website🤗HF

    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)
    $1.20Input: $0.60 | Output: $3.00
    Context Window
    262.14k tokens
    Read our data collection methodology

    Frequently Asked Questions about Qwen3.6-Plus vs kimi-k2.5

    Qwen3.6-Plus is cheaper than kimi-k2.5. Qwen3.6-Plus has a blended cost of $1.13/1M tokens, which is about 1.1x cheaper than kimi-k2.5 at $1.20/1M tokens.

    Qwen3.6-Plus is better for coding tasks on this benchmark. It scores 56.6% 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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