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
- Datasette Apps: Host custom HTML applications inside Datasette - 18th June 2026
- GLM-5.2 is probably the most powerful text-only open weights LLM - 17th June 2026
- Publishing WASM wheels to PyPI for use with Pyodide - 13th June 2026