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Scale is not the only driver of AI progress. Epoch AI measures how much training compute it takes to reach a fixed level of language-model performance, and finds that requirement falling fast: pre-training compute efficiency doubles every 7.6 months
Verified 2026-08-15
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- Epoch AI fits a trend through the models whose context windows ranked among the ten longest on their release date, and finds that since mid-2023 the frontier context window has been getting about 30× longer every year
- Of the notable AI models released in 2025, Stanford's AI Index counts over 90% as coming from industry
- Across 42 notable language models, Epoch AI estimates frontier training costs have risen from roughly $2 million for GPT-3 to up to nearly $390 million per run