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
- New release of LLM adds support for reasoning traces, OpenAI Responses, server-side tools, and smarter logging - 4th August 2026
- Stateless MCP has recaptured my interest (and inspired mcp-explorer and datasette-mcp) - 31st July 2026
- OpenAI’s accidental cyberattack against Hugging Face is science fiction that happened - 22nd July 2026