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OpenAIGPT-5.4VSZ.ai (Zhipu AI)GLM-4.5

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

Our Take

We recommend GPT-5.4 if you need peak intelligence for complex complex codebases, multi-file repositories, and architectural planning, or the 5.6x cheaper GLM-4.5 if your workflow is limited to multi-file code and clearly defined tasks. While GPT-5.4 holds a major reasoning advantage, GLM-4.5 is optimized for high-volume budget pipelines. Choose GPT-5.4 for architectural codebase planning, or GLM-4.5 to maximize your budget for basic scripts.
WHY?
Benchmark Calculations & Evidence:
  • Coding Evaluation: GPT-5.4 was evaluated on SWE-bench Pro (scoring 57.7%), while GLM-4.5 was evaluated on SWE-bench Verified (scoring 64.2%).
  • Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. GPT-5.4 scored 92.8%, while GLM-4.5 scored 79.9%.
  • Cost Efficiency: GLM-4.5 pricing ($0.6/M input, $2.2/M output) is 5.6x cheaper than GPT-5.4 ($2.5/M input, $15/M output).
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    Model Specs

    GPT-5.4

    Benchmarks & Scores

    Coding (swe-bench-pro)
    57.7%

    complex codebases, multi-file repositories, and architectural planning

    Reasoning (gpqa-diamond)Winner (+12.9%)
    92.8%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)
    $5.63Input: $2.50 | Output: $15.00
    Context WindowLarger
    1.05M tokens
    Model Specs

    GLM-4.5

    Open SourceAPI Available

    Benchmarks & Scores

    Coding (swe-bench-verified)
    64.2%

    multi-file code and clearly defined tasks

    Reasoning (gpqa-diamond)
    79.9%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)5.6x cheaper
    $1.00Input: $0.60 | Output: $2.20
    Context Window
    131.07k tokens

    Frequently Asked Questions about GPT-5.4 vs GLM-4.5

    GLM-4.5 is cheaper than GPT-5.4. GLM-4.5 has a blended cost of $1.00/1M tokens, which is about 5.6x cheaper than GPT-5.4 at $5.63/1M tokens.

    For coding tasks, GPT-5.4 scores 57.7% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning), while GLM-4.5 scores 64.2% on swe-bench-verified (multi-file code and clearly defined tasks).

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