Text model · phi
Phi-4-mini 3.8B requirements
phi family · 3.8B params · released Feb 2025 · 931.9K Ollama pulls. Minimum to run at Q4_K_M: Apple M1 (8GB).
Quantization sizes
| Quantization | Size on disk |
|---|---|
| Q2_K | 1.6 GB est |
| Q3_K_M | 1.9 GB est |
| Q4_K_M (default) | 2.49 GB |
| Q5_K_M | 2.7 GB est |
| Q6_K | 3.1 GB est |
| Q8_0 | 4.08 GB |
| FP16 | 7.6 GB est |
Lower quant = smaller and faster, slightly lower quality. Q4_K_M is the common default.
Run it
ollama run phi4-mini:3.8b llama-cli -hf bartowski/microsoft_Phi-4-mini-instruct-GGUF:Q4_K_M lms get bartowski/microsoft_Phi-4-mini-instruct-GGUF Which devices can run Phi-4-mini 3.8B?
Apple Silicon Macs
RAM-only laptops
iPhone & iPad
Android
NVIDIA GPUs
AMD GPUs
FAQ
How much VRAM or RAM does Phi-4-mini 3.8B need?
At Q4_K_M, Phi-4-mini 3.8B needs about 3.8 GB (weights ~2.49 GB + KV cache + overhead) at a 4k context. At Q8_0 budget ~5.4 GB.
Can Phi-4-mini 3.8B run on a laptop?
Yes, Phi-4-mini 3.8B fits on a 16 GB machine at Q4_K_M and runs on Apple Silicon or a 12 GB+ GPU comfortably.
Can I use Phi-4-mini 3.8B commercially?
Yes. Phi-4-mini 3.8B is licensed MIT, which permits commercial use.
Released February 2025 by Microsoft. Dense decoder-only transformer with 200K vocabulary. 128K context. Q4_K_M=2.49GB and Q8_0=4.08GB from bartowski HF repo (microsoft_Phi-4-mini-instruct-GGUF). Requires Ollama 0.5.13+.
Sources
Memory figures are estimates. See methodology.