MetaLlama-3.1 405BVSZ.ai (Zhipu AI)GLM-4.7
Our Take
We recommend GLM-4.7 if you need peak intelligence and a much larger context window for full-repo analysis, or the free Llama-3.1 405B if you want zero API costs and total offline privacy. While GLM-4.7 offers superior reasoning capability (hostable locally or via API), Llama-3.1 405B runs entirely on your own local hardware. Choose GLM-4.7 for repository-scale analysis, or Llama-3.1 405B for zero-cost offline privacy and basic standalone code completion and simple functions.
▶WHY?
Benchmark Calculations & Evidence:
Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. GLM-4.7 scored 85.7%, while Llama-3.1 405B scored 50.7% (+35.0% gap).
Coding Performance: Evaluated on different benchmarks. Llama-3.1 405B scored 89% on HumanEval (basic standalone code completion and simple functions), while GLM-4.7 scored 73.8% on SWE-bench Verified (multi-file code and clearly defined tasks).
Context Window: GLM-4.7 supports a 203k context window, while Llama-3.1 405B supports 131k.
Hosting Model: Llama-3.1 405B runs locally for $0 API costs, while GLM-4.7 is a cloud API.
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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-verified)
73.8%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)Winner (+35.0%)
85.7%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$1.00Input: $0.60 | Output: $2.20Context WindowLarger
202.75k tokensFrequently Asked Questions about Llama-3.1 405B vs GLM-4.7
For coding tasks, Llama-3.1 405B scores 89% on human-eval (basic standalone code completion and simple functions), while GLM-4.7 scores 73.8% on swe-bench-verified (multi-file code and clearly defined tasks).
Related Matchups
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