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Mistral AIMistral Large 3VSOpenAIGPT-5.4 nano

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

Our Take

We recommend Mistral Large 3 for complex scripting single-file apps or clearly defined functions, or the 1.6x cheaper GPT-5.4 nano if your budget requires optimizing costs for very high-volume pipelines. While Mistral Large 3 offers a clear reasoning advantage, it carries a moderate price premium. Choose Mistral Large 3 for scripting single-file apps or clearly defined functions, or GPT-5.4 nano to save on API costs for simple scripts.
▶WHY?
Benchmark Calculations & Evidence:
  • Coding Evaluation: Mistral Large 3 was evaluated on LiveCodeBench (scoring 34.4%), 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. Mistral Large 3 scored 85.5%, while GPT-5.4 nano scored 82.8%.
  • Cost Efficiency: GPT-5.4 nano pricing ($0.2/M input, $1.25/M output) is 1.6x cheaper than Mistral Large 3 ($0.5/M input, $1.5/M output).
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    Model Specs

    Mistral Large 3

    Open SourceAPI Available
    Website🤗HF

    Benchmarks & Scores

    Coding (live-code-bench)
    34.4%

    scripting single-file apps or clearly defined functions

    Reasoning (gpqa-diamond)Winner (+2.7%)
    85.5%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)
    $0.75Input: $0.50 | Output: $1.50
    Context Window
    262.14k 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)1.6x cheaper
    $0.46Input: $0.20 | Output: $1.25
    Context WindowLarger
    400k tokens
    Read our data collection methodology

    Frequently Asked Questions about Mistral Large 3 vs GPT-5.4 nano

    GPT-5.4 nano is cheaper than Mistral Large 3. GPT-5.4 nano has a blended cost of $0.46/1M tokens, which is about 1.6x cheaper than Mistral Large 3 at $0.75/1M tokens.

    For coding tasks, Mistral Large 3 scores 34.4% on live-code-bench (scripting single-file apps or clearly defined functions), while GPT-5.4 nano scores 52.4% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning).

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