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DeepSeekDeepSeek V4 FlashVSOpenAIGPT-5 mini

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

Our Take

We recommend choosing DeepSeek V4 Flash as it delivers superior coding capability while matching the reasoning accuracy of GPT-5 mini at a 3.9x API cost saving. Choose DeepSeek V4 Flash for superior overall value and coding efficiency.
▶WHY?
Benchmark Calculations & Evidence:
  • Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. DeepSeek V4 Flash scored 49.1%, while GPT-5 mini scored 45.7%.
  • Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. DeepSeek V4 Flash scored 80%, while GPT-5 mini scored 81.6%.
  • Cost Efficiency: GPT-5 mini pricing ($0.25/M input, $2/M output) is 3.9x cheaper than DeepSeek V4 Flash ($0.14/M input, $0.28/M output).
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    Model Specs

    DeepSeek V4 Flash

    Open SourceAPI Available
    Website🤗HF

    Benchmarks & Scores

    Coding (swe-bench-pro)Winner (+3.4%)
    49.1%

    complex codebases, multi-file repositories, and architectural planning

    Reasoning (gpqa-diamond)
    80%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)3.9x cheaper
    $0.17Input: $0.14 | Output: $0.28
    Context WindowLarger
    1.05M tokens
    Model Specs

    GPT-5 mini

    Website

    Benchmarks & Scores

    Coding (swe-bench-pro)
    45.7%

    complex codebases, multi-file repositories, and architectural planning

    Reasoning (gpqa-diamond)Winner (+1.6%)
    81.6%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)
    $0.69Input: $0.25 | Output: $2.00
    Context Window
    400k tokens
    Read our data collection methodology

    Frequently Asked Questions about DeepSeek V4 Flash vs GPT-5 mini

    DeepSeek V4 Flash is cheaper than GPT-5 mini. DeepSeek V4 Flash has a blended cost of $0.17/1M tokens, which is about 3.9x cheaper than GPT-5 mini at $0.69/1M tokens.

    DeepSeek V4 Flash is better for coding tasks on this benchmark. It scores 49.1% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning) compared to GPT-5 mini which scores 45.7%.

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