Phi 3.5 Family — Local AI Model by Microsoft

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 20 sierpnia 2024

Superseded model. Phi 3.5 Family has been superseded by Phi-4 Family. This page is kept for reference; the newer family is a better starting point. View Phi-4 Family →

Wysoce wydajne małe modele językowe (SLM) od Microsoftu. Idealne dla urządzeń mobilnych, edge computingu i środowisk z niskim VRAM bez rezygnowania z podstawowego rozumowania.

Licence

LicenceWhat it permitsApplies to
MITCommercial use permitted
Commercial use permitted. No usage restrictions beyond attribution.
Phi 3.5 Mini

Hardware Requirements

Phi 3.5 MiniMin 3 GB VRAM · Q4_K_M · 128,000 ctx · ollama run phi3.5

Recommended GPU

The cheapest GPU that runs Phi 3.5 Family locally (min 3 GB VRAM) is the Intel Arc B570 (10 GB).

Ujawnienie afiliacyjne: Niektóre odnośniki na tej stronie to linki afiliacyjne — jeśli dokonasz zakupu za ich pośrednictwem, LLM Configurator może otrzymać prowizję bez dodatkowych kosztów dla Ciebie. Jako uczestnik programu Amazon Associates, LLM Configurator zarabia na kwalifikujących się zakupach.
Intel Arc B570 10GB
10 GB VRAM · 150 W board power
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

How to Run Locally

Install Ollama then run: ollama run phi3.5

Minimum VRAM: 3 GB. For best results use Q4_K_M quantization.

Phi 3.5 Family — Frequently Asked Questions

How much VRAM does Phi 3.5 Family need?

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.

Can I run Phi 3.5 Family on an RTX 4090 (24 GB)?

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.

What quantization should I use for Phi 3.5 Family?

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.

How do I run Phi 3.5 Family with Ollama?

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.

Can I Run Phi 3.5 Family on My GPU?