OpenAIGPT-5.4 nanoVSZ.ai (Zhipu AI)GLM-5
Our Take
We recommend GLM-5 if you need peak intelligence for complex multi-file code and clearly defined tasks, or the 3.4x cheaper GPT-5.4 nano if your workflow is limited to complex codebases, multi-file repositories, and architectural planning. While GLM-5 holds a major reasoning advantage, GPT-5.4 nano is optimized for high-volume budget pipelines. Choose GLM-5 for multi-file code and clearly defined tasks, or GPT-5.4 nano to maximize your budget for basic scripts.
▶WHY?
Benchmark Calculations & Evidence:
Coding Evaluation: GPT-5.4 nano was evaluated on SWE-bench Pro (scoring 52.4%), while GLM-5 was evaluated on SWE-bench Verified (scoring 77.8%).
Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. GLM-5 scored 86%, while GPT-5.4 nano scored 82.8%.
Cost Efficiency: GPT-5.4 nano pricing ($0.2/M input, $1.25/M output) is 3.4x cheaper than GLM-5 ($1/M input, $3.2/M output).
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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)3.4x cheaper
$0.46Input: $0.20 | Output: $1.25Context WindowLarger
400k tokensBenchmarks & Scores
Coding (swe-bench-verified)
77.8%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)Winner (+3.2%)
86%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$1.55Input: $1.00 | Output: $3.20Context Window
202.75k tokensFrequently Asked Questions about GPT-5.4 nano vs GLM-5
GPT-5.4 nano is cheaper than GLM-5. GPT-5.4 nano has a blended cost of $0.46/1M tokens, which is about 3.4x cheaper than GLM-5 at $1.55/1M tokens.
For coding tasks, GPT-5.4 nano scores 52.4% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning), while GLM-5 scores 77.8% on swe-bench-verified (multi-file code and clearly defined tasks).
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