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
- Qwen3.6-35B-A3B on my laptop drew me a better pelican than Claude Opus 4.7 - 16th April 2026
- Meta's new model is Muse Spark, and meta.ai chat has some interesting tools - 8th April 2026
- Anthropic's Project Glasswing - restricting Claude Mythos to security researchers - sounds necessary to me - 7th April 2026