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GoogleGemini 3.5 FlashVSOpenAIGPT-5.4 nano

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

Our Take

We recommend Gemini 3.5 Flash if you need peak intelligence for reasoning and coding tasks, or the 7.3x cheaper GPT-5.4 nano to optimize your budget for high-volume pipelines. While Gemini 3.5 Flash holds a clear performance lead, it carries a heavy price premium. Choose Gemini 3.5 Flash for complex logic, or GPT-5.4 nano for budget efficiency.
▶WHY?
Benchmark Calculations & Evidence:
  • Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. Gemini 3.5 Flash scored 55.1%, while GPT-5.4 nano scored 52.4%.
  • Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. Gemini 3.5 Flash scored 92.2%, while GPT-5.4 nano scored 82.8%.
  • Cost Efficiency: GPT-5.4 nano pricing ($0.2/M input, $1.25/M output) is 7.3x cheaper than Gemini 3.5 Flash ($1.5/M input, $9/M output).
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    Model Specs

    Gemini 3.5 Flash

    Website

    Benchmarks & Scores

    Coding (swe-bench-pro)Winner (+2.7%)
    55.1%

    complex codebases, multi-file repositories, and architectural planning

    Reasoning (gpqa-diamond)Winner (+9.4%)
    92.2%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)
    $3.38Input: $1.50 | Output: $9.00
    Context WindowLarger
    1.05M tokens
    Model Specs

    GPT-5.4 nano

    Website

    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)7.3x cheaper
    $0.46Input: $0.20 | Output: $1.25
    Context Window
    400k tokens
    Read our data collection methodology

    Frequently Asked Questions about Gemini 3.5 Flash vs GPT-5.4 nano

    GPT-5.4 nano is cheaper than Gemini 3.5 Flash. GPT-5.4 nano has a blended cost of $0.46/1M tokens, which is about 7.3x cheaper than Gemini 3.5 Flash at $3.38/1M tokens.

    Gemini 3.5 Flash is better for coding tasks on this benchmark. It scores 55.1% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning) compared to GPT-5.4 nano which scores 52.4%.

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