31st January 2026
Originally in 2019, GPT-2 was trained by OpenAI on 32 TPU v3 chips for 168 hours (7 days), with $8/hour/TPUv3 back then, for a total cost of approx. $43K. It achieves 0.256525 CORE score, which is an ensemble metric introduced in the DCLM paper over 22 evaluations like ARC/MMLU/etc.
As of the last few improvements merged into nanochat (many of them originating in modded-nanogpt repo), I can now reach a higher CORE score in 3.04 hours (~$73) on a single 8XH100 node. This is a 600X cost reduction over 7 years, i.e. the cost to train GPT-2 is falling approximately 2.5X every year.
Recent articles
- DeepSeek V4 - almost on the frontier, a fraction of the price - 24th April 2026
- Extract PDF text in your browser with LiteParse for the web - 23rd April 2026
- A pelican for GPT-5.5 via the semi-official Codex backdoor API - 23rd April 2026