OpenAIGPT-5.4 nanoVSZ.ai (Zhipu AI)GLM-5.2
Our Take
We recommend GLM-5.2 if you need peak intelligence for reasoning and coding tasks, or the 4.6x cheaper GPT-5.4 nano to optimize your budget for high-volume pipelines. While GLM-5.2 holds a clear performance lead, it carries a heavy price premium. Choose GLM-5.2 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. GLM-5.2 scored 62.1%, while GPT-5.4 nano scored 52.4%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. GLM-5.2 scored 91.2%, while GPT-5.4 nano scored 82.8%.
Cost Efficiency: GPT-5.4 nano pricing ($0.2/M input, $1.25/M output) is 4.6x cheaper than GLM-5.2 ($1.4/M input, $4.4/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)4.6x cheaper
$0.46Input: $0.20 | Output: $1.25Context Window
400k tokensBenchmarks & Scores
Coding (swe-bench-pro)Winner (+9.7%)
62.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+8.4%)
91.2%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$2.15Input: $1.40 | Output: $4.40Context WindowLarger
1.05M tokensFrequently Asked Questions about GPT-5.4 nano vs GLM-5.2
GPT-5.4 nano is cheaper than GLM-5.2. GPT-5.4 nano has a blended cost of $0.46/1M tokens, which is about 4.6x cheaper than GLM-5.2 at $2.15/1M tokens.
GLM-5.2 is better for coding tasks on this benchmark. It scores 62.1% 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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