# Phi-4 14B: RAM and VRAM requirements

> Phi-4 14B is a 14B phi model. At Q4_K_M it needs about **10.8 GB** to run and fits **23 of 39** tracked devices. Minimum to run: Nvidia GeForce RTX 3060 (12GB).

Last validated: 2026-06-15. Sources: Ollama, HuggingFace GGUF repos, vendor specs.

## Memory by quantization
| Quant | On disk | To run (4k context) |
| --- | --- | --- |
| Q4_K_M | 9.05 GB | ~10.8 GB |
| Q8_0 | 15.58 GB | ~17.3 GB |

Memory = weights + KV cache + ~0.8 GB runtime overhead, and varies ±15% with context length.

## Will it run on my device?
- **Apple M1 (8GB)** (8 GB): No, not enough memory
- **Generic Android Phone (8GB RAM)** (8 GB): No, not enough memory
- **iPhone 17 Pro** (12 GB): No, not enough memory
- **Nvidia GeForce RTX 4080 (16GB)** (16 GB): Yes, it runs
- **Google Pixel 10 Pro** (16 GB): No, not enough memory
- **Nvidia GeForce RTX 4090 (24GB)** (24 GB): Yes, it runs — room for Q8_0
- **Apple M4 Pro (48GB)** (48 GB): Yes, it runs — room for FP16
- **Apple M3 Ultra (256GB)** (256 GB): Yes, it runs — room for FP16

Full table of all 39 devices: https://localmodel.run/model/phi-4-14b

## How to run
Quickest path: `ollama run phi4:14b`. On Mac, LM Studio (ships MLX) is fastest; on Linux, Ollama for chat or vLLM to serve; on Windows, LM Studio or Ollama.

## Details
- Parameters: 14B
- Default context: 16k tokens
- License: MIT (commercial use: yes)
- Released: 2024-12
- HuggingFace: 714,082 downloads/mo, 2254 likes

## FAQ
### How much VRAM or RAM does Phi-4 14B need?
About 10.8 GB at Q4_K_M (weights 9.05 GB + KV cache + overhead) at a 4k context. Budget ~17.3 GB for Q8_0.
### Can Phi-4 14B run on a laptop?
Phi-4 14B is large; you need a high-memory Mac or a 24 GB+ GPU at Q4_K_M.
### Can I use Phi-4 14B commercially?
Yes, MIT permits commercial use.

Sources: https://ollama.com/library/phi4, https://ollama.com/library/phi4/tags, https://huggingface.co/bartowski/phi-4-GGUF, https://lmarena.ai/leaderboard
More: https://localmodel.run/model/phi-4-14b