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
- Porting the Moebius 0.2B image inpainting model to run in the browser with Claude Code - 22nd June 2026
- sqlite-utils 4.0rc1 adds migrations and nested transactions - 21st June 2026
- Datasette Apps: Host custom HTML applications inside Datasette - 18th June 2026