Z.ai (Zhipu AI)GLM-4.6VSZ.ai (Zhipu AI)GLM-5
Our Take
We recommend GLM-4.6 for practical local execution on standard developer hardware, or GLM-5 if you need peak reasoning and have the VRAM (or a cloud API) to host it. While GLM-5 offers frontier capability, its massive parameter size makes it extremely difficult to host locally. Choose GLM-4.6 for standard local setups, or GLM-5 for peak reasoning.
▶WHY?
Benchmark Calculations & Evidence:
Model Size: GLM-5 is a massive 754B parameter model requiring heavy GPU infrastructure, while GLM-4.6 is a 357B parameter model.
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Benchmarks & Scores
Coding (swe-bench-verified)
68%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)
82.9%graduate-level science QA
Cost & Context
Cost (per 1M tokens)1.6x cheaper
$1.00Input: $0.60 | Output: $2.20Context Window
202.75k tokensBenchmarks & Scores
Coding (swe-bench-verified)Winner (+9.8%)
77.8%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)Winner (+3.1%)
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 GLM-4.6 vs GLM-5
GLM-4.6 is cheaper than GLM-5. GLM-4.6 has a blended cost of $1.00/1M tokens, which is about 1.6x cheaper than GLM-5 at $1.55/1M tokens.
GLM-5 is better for coding tasks on this benchmark. It scores 77.8% on swe-bench-verified (multi-file code and clearly defined tasks) compared to GLM-4.6 which scores 68%.
Related Matchups
Explore similar comparisons for GLM-4.6 and GLM-5.
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