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
- The Pelican comparison grid for Astra is pretty interesting - 4th September 2026
- OpenAI's rogue agents were caught communicating via public wikis - 4th September 2026
- Claude's new system prompt really doesn't want to reproduce song lyrics - 2nd September 2026