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AnthropicClaude Opus 4.7VSOpenAIGPT-5.4 nano

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 21.6x cheaper GPT-5.4 nano 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 GPT-5.4 nano 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 GPT-5.4 nano scored 52.4%.
  • Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. Claude Opus 4.7 scored 94.2%, while GPT-5.4 nano scored 82.8%.
  • Cost Efficiency: GPT-5.4 nano pricing ($0.2/M input, $1.25/M output) is 21.6x cheaper than Claude Opus 4.7 ($5/M input, $25/M output).
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    Model Specs

    Claude Opus 4.7

    Website

    Benchmarks & Scores

    Coding (swe-bench-pro)Winner (+11.9%)
    64.3%

    complex codebases, multi-file repositories, and architectural planning

    Reasoning (gpqa-diamond)Winner (+11.4%)
    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

    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)21.6x cheaper
    $0.46Input: $0.20 | Output: $1.25
    Context Window
    400k tokens
    Read our data collection methodology

    Frequently Asked Questions about Claude Opus 4.7 vs GPT-5.4 nano

    GPT-5.4 nano is cheaper than Claude Opus 4.7. GPT-5.4 nano has a blended cost of $0.46/1M tokens, which is about 21.6x 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 GPT-5.4 nano which scores 52.4%.

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