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I trained a small transformer in 1.5hrs and it beats many LLMs

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Why This Matters

This breakthrough demonstrates that small, efficient transformers can be trained rapidly and outperform many larger language models, emphasizing the importance of sample efficiency and cost reduction in AI development. It opens new possibilities for accessible, high-performance AI research, especially in resource-constrained environments.

Key Takeaways

I trained a small transformer from scratch in 1.5hrs on a 5090

Beats many LLMs, and scores the same as TRM/HRM

This is an upgrade to my previous model

Faster, better, cheaper and still open source.

Also gets 7% on ARC-2

Discussion on Twitter, Code on github

Performance on ARC-1 public eval. I only compare against models that do similar test time training

This is the 3rd blog in a series of works on ARC-AGI. Prev: Blog 2, Blog 1.

Many ppl thought the prev result was impossible. It got attention from top researchers and went viral on X. Eg: Discussions by Lucas Beyer, Jeremy Howard, Rohan Anil, and comments by many others.

Why work on this?

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