Written by Jakub Rusinowski · Last updated August 20, 2024
Microsoft's highly efficient small language models (SLMs). Perfect for mobile devices, edge computing, and low-VRAM environments without sacrificing basic reasoning.
| Licence | What it permits | Applies to |
|---|---|---|
MIT | Commercial use permitted Commercial use permitted. No usage restrictions beyond attribution. | Phi 3.5 Mini |
| Phi 3.5 Mini | Min 3 GB VRAM · Q4_K_M · 128,000 ctx · ollama run phi3.5 |
The cheapest GPU that runs Phi 3.5 Family locally (min 3 GB VRAM) is the Intel Arc B570 (10 GB).
Install Ollama then run: ollama run phi3.5
Minimum VRAM: 3 GB. For best results use Q4_K_M quantization.
Phi 3.5 Family needs about 3 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Phi 3.5 Mini (3 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Yes — Phi 3.5 Family runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.
Q4_K_M is the best balance of quality and VRAM for Phi 3.5 Family in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
Install Ollama, then run: ollama run phi3.5. This downloads Phi 3.5 Family and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.