OpenAIGPT-5.4VSZ.ai (Zhipu AI)GLM-5.2
Our Take
We recommend choosing GLM-5.2 as it delivers superior coding capability while matching the reasoning accuracy of GPT-5.4 at a 2.6x API cost saving. Choose GLM-5.2 for superior overall value and coding efficiency.
▶WHY?
Benchmark Calculations & Evidence:
Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. GPT-5.4 scored 57.7%, while GLM-5.2 scored 62.1%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. GPT-5.4 scored 92.8%, while GLM-5.2 scored 91.2%.
Cost Efficiency: GPT-5.4 pricing ($2.5/M input, $15/M output) is 2.6x cheaper than GLM-5.2 ($1.4/M input, $4.4/M output).
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Benchmarks & Scores
Coding (swe-bench-pro)
57.7%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+1.6%)
92.8%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$5.63Input: $2.50 | Output: $15.00Context WindowLarger
1.05M tokensBenchmarks & Scores
Coding (swe-bench-pro)Winner (+4.4%)
62.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
91.2%graduate-level science QA
Cost & Context
Cost (per 1M tokens)2.6x cheaper
$2.15Input: $1.40 | Output: $4.40Context Window
1.05M tokensFrequently Asked Questions about GPT-5.4 vs GLM-5.2
GLM-5.2 is cheaper than GPT-5.4. GLM-5.2 has a blended cost of $2.15/1M tokens, which is about 2.6x cheaper than GPT-5.4 at $5.63/1M 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 which scores 57.7%.
Related Matchups
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