Z.ai (Zhipu AI)GLM-5VSZ.ai (Zhipu AI)GLM-5.2
Our Take
We recommend GLM-5.2 for complex complex codebases, multi-file repositories, and architectural planning, or the 1.4x cheaper GLM-5 if your budget requires optimizing costs for very high-volume pipelines. While GLM-5.2 offers a clear reasoning advantage, it carries a moderate price premium. Choose GLM-5.2 for architectural codebase planning, or GLM-5 to save on API costs for simple scripts.
▶WHY?
Benchmark Calculations & Evidence:
Coding Evaluation: GLM-5 was evaluated on SWE-bench Verified (scoring 77.8%), while GLM-5.2 was evaluated on SWE-bench Pro (scoring 62.1%).
Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. GLM-5.2 scored 91.2%, while GLM-5 scored 86%.
Cost Efficiency: GLM-5 pricing ($1/M input, $3.2/M output) is 1.4x cheaper than GLM-5.2 ($1.4/M input, $4.4/M output).
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Benchmarks & Scores
Coding (swe-bench-verified)
77.8%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)
86%graduate-level science QA
Cost & Context
Cost (per 1M tokens)1.4x cheaper
$1.55Input: $1.00 | Output: $3.20Context Window
202.75k tokensBenchmarks & Scores
Coding (swe-bench-pro)
62.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+5.2%)
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 GLM-5 vs GLM-5.2
GLM-5 is cheaper than GLM-5.2. GLM-5 has a blended cost of $1.55/1M tokens, which is about 1.4x cheaper than GLM-5.2 at $2.15/1M tokens.
For coding tasks, GLM-5 scores 77.8% on swe-bench-verified (multi-file code and clearly defined tasks), while GLM-5.2 scores 62.1% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning).
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