23rd April 2024
We introduce phi-3-mini, a 3.8 billion parameter language model trained on 3.3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal testing, rivals that of models such as Mixtral 8x7B and GPT-3.5 (e.g., phi-3-mini achieves 69% on MMLU and 8.38 on MT-bench), despite being small enough to be deployed on a phone.
Recent articles
- Claude Opus 4.8: "a modest but tangible improvement" - 28th May 2026
- I think Anthropic and OpenAI have found product-market fit - 27th May 2026
- Notes on Pope Leo XIV's encyclical on AI - 25th May 2026