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
- Experimenting with Starlette 1.0 with Claude skills - 22nd March 2026
- Profiling Hacker News users based on their comments - 21st March 2026
- Thoughts on OpenAI acquiring Astral and uv/ruff/ty - 19th March 2026