Z.ai (Zhipu AI)GLM-4.5VSZ.ai (Zhipu AI)GLM-5.2
Our Take
We recommend GLM-4.5 for practical local execution on standard developer hardware, or GLM-5.2 if you need peak reasoning and have the VRAM (or a cloud API) to host it. While GLM-5.2 offers frontier capability, its massive parameter size makes it extremely difficult to host locally. Choose GLM-4.5 for standard local setups, or GLM-5.2 for peak reasoning.
▶WHY?
Benchmark Calculations & Evidence:
Model Size: GLM-5.2 is a massive 753B parameter model requiring heavy GPU infrastructure, while GLM-4.5 is a 358B parameter model.
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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)2.1x cheaper
$1.00Input: $0.60 | Output: $2.20Context Window
131.07k tokensBenchmarks & Scores
Coding (swe-bench-pro)
62.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+11.3%)
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-4.5 vs GLM-5.2
GLM-4.5 is cheaper than GLM-5.2. GLM-4.5 has a blended cost of $1.00/1M tokens, which is about 2.1x cheaper than GLM-5.2 at $2.15/1M tokens.
For coding tasks, GLM-4.5 scores 64.2% 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).
Related Matchups
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