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
- Perhaps not Boring Technology after all - 9th March 2026
- Can coding agents relicense open source through a “clean room” implementation of code? - 5th March 2026
- Something is afoot in the land of Qwen - 4th March 2026