Models / Phi
Phi-4-mini 3.8B
general-chaton-devicereasoningcodinggpu-8gbgpu-16gbgpu-24gbgpu-48gbapple-silicon-16gbapple-silicon-32gbcpu-16gbcpu-32gbdatacenter
Strengths
MIT license, 67% MMLU at 3.8B. Inherits the Phi reasoning lineage in a small footprint. 128K context, 200K-token vocabulary for multilingual support. Function-calling support.
Weaknesses
Not a reasoning specialist like Phi-4 Reasoning 14B; the 'mini' is general-purpose. Refusal calibration leans cautious.
Phi-4-mini is the small Phi for general use. Where Phi-4 Reasoning 14B is a dedicated reasoner that's not great at chat, Phi-4-mini at 3.8B is a balanced generalist with the same MIT license and a longer context window than most rivals at this size.
The 200K-token vocabulary is unusual at this size and pays off for multilingual data. Built-in function-calling makes it a credible small agent base.
When to pick it
- MIT license is required and you want the smallest competent open model.
- On-device or low-end GPU deployment where the Phi family's reasoning bias still helps.
- Built-in function calling for lightweight agent flows.
When to skip it
- You need actual heavy reasoning. Pick Phi-4 Reasoning 14B.
- You want one model with the most community fine-tunes. Llama 3.2 3B has more.