MetaLlama-3.1 8BVSMetaLlama-3.3-70B
Our Take
We recommend Llama-3.3-70B for superior reasoning capability, or Llama-3.1 8B for faster local inference on smaller GPU hardware. While both models run locally for zero API costs, Llama-3.3-70B carries a larger parameter memory footprint. Choose Llama-3.3-70B if you have the VRAM to support it, or Llama-3.1 8B for consumer-grade hardware compatibility.
▶WHY?
Benchmark Calculations & Evidence:
Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. Llama-3.3-70B scored 50.5%, while Llama-3.1 8B scored 30.4% (+20.1% gap).
Coding Performance: Both models were evaluated on the HumanEval benchmark. Llama-3.3-70B scored 88.4%, while Llama-3.1 8B scored 72.6% (+15.8% gap).
Hardware Footprint: Llama-3.3-70B is a 70B parameter model requiring more VRAM, while Llama-3.1 8B is a 8B parameter model.
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Benchmarks & Scores
Coding (human-eval)
72.6%basic standalone code completion and simple functions
Reasoning (gpqa-diamond)
30.4%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
Self HostLocal execution (zero API fees)Context Window
131.07k tokensBenchmarks & Scores
Coding (human-eval)Winner (+15.8%)
88.4%basic standalone code completion and simple functions
Reasoning (gpqa-diamond)Winner (+20.1%)
50.5%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
Self HostLocal execution (zero API fees)Context Window
131.07k tokensFrequently Asked Questions about Llama-3.1 8B vs Llama-3.3-70B
Llama-3.3-70B is better for coding tasks on this benchmark. It scores 88.4% on human-eval (basic standalone code completion and simple functions) compared to Llama-3.1 8B which scores 72.6%.
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