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GoogleGemini 3 FlashVSOpenAIGPT-5.4 nano

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

Our Take

We recommend Gemini 3 Flash for complex multi-file code and clearly defined tasks, or the 2.4x cheaper GPT-5.4 nano if your budget requires optimizing costs for very high-volume pipelines. While Gemini 3 Flash offers a clear reasoning advantage, it carries a moderate price premium. Choose Gemini 3 Flash for multi-file code and clearly defined tasks, or GPT-5.4 nano to save on API costs for simple scripts.
WHY?
Benchmark Calculations & Evidence:
  • Coding Evaluation: Gemini 3 Flash was evaluated on SWE-bench Verified (scoring 78%), while GPT-5.4 nano was evaluated on SWE-bench Pro (scoring 52.4%).
  • Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. Gemini 3 Flash scored 90.4%, while GPT-5.4 nano scored 82.8%.
  • Cost Efficiency: GPT-5.4 nano pricing ($0.2/M input, $1.25/M output) is 2.4x cheaper than Gemini 3 Flash ($0.5/M input, $3/M output).
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    Model Specs

    Gemini 3 Flash

    Benchmarks & Scores

    Coding (swe-bench-verified)
    78%

    multi-file code and clearly defined tasks

    Reasoning (gpqa-diamond)Winner (+7.6%)
    90.4%

    graduate-level science QA

    Cost & Context

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

    GPT-5.4 nano

    Benchmarks & Scores

    Coding (swe-bench-pro)
    52.4%

    complex codebases, multi-file repositories, and architectural planning

    Reasoning (gpqa-diamond)
    82.8%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)2.4x cheaper
    $0.46Input: $0.20 | Output: $1.25
    Context Window
    400k tokens

    Frequently Asked Questions about Gemini 3 Flash vs GPT-5.4 nano

    GPT-5.4 nano is cheaper than Gemini 3 Flash. GPT-5.4 nano has a blended cost of $0.46/1M tokens, which is about 2.4x cheaper than Gemini 3 Flash at $1.13/1M tokens.

    For coding tasks, Gemini 3 Flash scores 78% on swe-bench-verified (multi-file code and clearly defined tasks), while GPT-5.4 nano scores 52.4% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning).

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