Unverified50% confidenceBenchmarkExact time
业界顶尖训练系统（如Google的PaLM训练、Meta的LLaMA训练）通常能达到40%-60%的MFU，而设计不当的系统可能低于30%
1
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50%
Confidence
Long-term
Relevance
8/21/2026
First Seen
Sources
Related Claims
Unverified大语言模型训练通常能达到40%–60%的MFU，而朴素RL训练的MFU往往不足5%75% similarUnverifiedAccording to a Google research report, the actual model training code in a production-level ML system often accounts for only 5% of the overall engineering effort, with the remaining 95% being supporting engineering infrastructure.68% similarUnverifiedFine-tuning typically requires only one percent or less of the original training cost to achieve domain performance close to that of a dedicated model.66% similarUnverifiedCurrent mainstream LLMs universally adopt a pre-training plus fine-tuning paradigm, first performing unsupervised pre-training on internet-scale corpora, then aligning with human preferences through techniques such as RLHF.66% similar
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