MetaLlama-3.1 405BVSZ.ai (Zhipu AI)GLM-5.1
Our Take
We recommend Llama-3.1 405B for practical local execution on standard developer hardware, or GLM-5.1 if you need peak reasoning and have the VRAM (or a cloud API) to host it. While GLM-5.1 offers frontier capability, its massive parameter size makes it extremely difficult to host locally. Choose Llama-3.1 405B for standard local setups, or GLM-5.1 for peak reasoning.
▶WHY?
Benchmark Calculations & Evidence:
Model Size: GLM-5.1 is a massive 754B parameter model requiring heavy GPU infrastructure, while Llama-3.1 405B is a 405B parameter model.
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Benchmarks & Scores
Coding (human-eval)
89%basic standalone code completion and simple functions
Reasoning (gpqa-diamond)
50.7%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
Self HostLocal execution (zero API fees)Context Window
131.07k tokensBenchmarks & Scores
Coding (swe-bench-pro)
58.4%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+35.5%)
86.2%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$2.15Input: $1.40 | Output: $4.40Context WindowLarger
202.75k tokensFrequently Asked Questions about Llama-3.1 405B vs GLM-5.1
For coding tasks, Llama-3.1 405B scores 89% on human-eval (basic standalone code completion and simple functions), while GLM-5.1 scores 58.4% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning).
Related Matchups
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