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
- Conceptual integrity and counting lines of code - 19th August 2026
- Qwen 3.8 27B is excellent, but it defaults to wildly overthinking things - 16th August 2026
- Now we have a timeline of the OpenAI accidental attack against Hugging Face - 7th August 2026