MetaLlama-3.1 70BVSZ.ai (Zhipu AI)GLM-5
Our Take
We recommend Llama-3.1 70B 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 Llama-3.1 70B 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 Llama-3.1 70B is a 70B parameter model.
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Benchmarks & Scores
Coding (human-eval)
80.5%basic standalone code completion and simple functions
Reasoning (gpqa-diamond)
46.7%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-verified)
77.8%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)Winner (+39.3%)
86%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$1.55Input: $1.00 | Output: $3.20Context WindowLarger
202.75k tokensFrequently Asked Questions about Llama-3.1 70B vs GLM-5
For coding tasks, Llama-3.1 70B scores 80.5% on human-eval (basic standalone code completion and simple functions), while GLM-5 scores 77.8% on swe-bench-verified (multi-file code and clearly defined tasks).
Related Matchups
Explore similar comparisons for Llama-3.1 70B and GLM-5.
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