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
- Kimi K3, and what we can still learn from the pelican benchmark - 16th July 2026
- The new GPT-5.6 family: Luna, Terra, Sol - 9th July 2026
- sqlite-utils 4.0, now with database schema migrations - 7th July 2026