# Chinchilla Projects at AI Tinkerers

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> Markdown URL: https://aitinkerers.org/technologies/chinchilla.md
> Technology record last updated: 2026-04-15T14:15:03Z
> Generated: 2026-10-25T09:07:04Z

DeepMind's 70B-parameter LLM: compute-optimal scaling, outperforming larger models like GPT-3 and Gopher with 4x the training data.

Chinchilla is DeepMind's 70-billion-parameter large language model (LLM), introduced in 2022 to redefine scaling laws (Source: *Training Compute-Optimal Large Language Models*). It challenges the 'bigger is better' trend: using the same compute budget as the 280B-parameter Gopher, Chinchilla achieves superior performance by training on 1.4 trillion tokens, four times more data. This compute-optimal approach yields an average accuracy of 67.5% on the MMLU benchmark and drastically cuts inference and fine-tuning costs: a clear win for efficiency.

- Official technology site: https://deepmind.google/discover/blog/an-empirical-analysis-of-compute-optimal-large-language-model-training/
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [LearnQuantum: AI Native Physics Engine](https://sf.aitinkerers.org/talks/rsvp_L724yA7lINQ)

- Event context: AI Tinkerers - San Francisco - Summer Edition - July 2024 — 2024-07-12 — San Francisco
- Public talk page: https://sf.aitinkerers.org/talks/rsvp_L724yA7lINQ

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