text model · phi · iOS

Can I run Phi-4 14B on iPhone 16 Pro?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Phi-4 14B needs ~10.8 GB even at Q4_K_M, but iPhone 16 Pro only has ~4.5 GB usable.

Needs ~10.8 GB Device usable ~4.5 GB

Needs ~10.8 GB even at Q4_K_M, but only ~4.5 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 6.3 GB: Phi-4 14B needs roughly 10.8 GB at Q4_K_M and iPhone 16 Pro leaves only about 4.5 GB usable for a model. The lightest tracked hardware that runs Phi-4 14B is the Nvidia GeForce RTX 3060 (12GB) at 12 GB. See Phi-4 14B on Nvidia GeForce RTX 3060 (12GB).

Q4_K_M needed: ~10.8 GB
Usable on device: ~4.5 GB
Device memory: 8 GB

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Which quant fits

Quant ladder vs ~4.5 GB usable

Q2_K

~7.6 GB

Q3_K_M

~8.5 GB

Q4_K_M

~10.8 GB

Q5_K_M

~11.7 GB

Q6_K

~13.2 GB

Q8_0

~17.3 GB

FP16

~29.7 GB

The line marks iPhone 16 Pro's ~4.5 GB budget; rungs past it are too large.

How to run it

On iOS use Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.).

Model phi

Parameters: 14B
Q4_K_M size: 9.05 GB
Q8_0 size: 15.58 GB
Context: 16k
Ollama tag: phi4:14b

Full Phi-4 14B requirements →

Device iOS

Memory: 8 GB unified
Usable for weights: ~4.5 GB
Power draw: ~12 W
Best runtime: llama.cpp + Metal (via PocketPal or Off Grid app)

Best models for iPhone 16 Pro →

What you can run instead

Run Phi-4 14B on other hardware

Nvidia GeForce RTX 3060 (12GB)Nvidia GeForce RTX 4070 (12GB)Nvidia GeForce RTX 4060 Ti (16GB)Nvidia GeForce RTX 4080 (16GB)16GB RAM Laptop (CPU/iGPU only)iPad Pro M4 (16GB, 1TB/2TB config)

FAQ

Can iPhone 16 Pro run Phi-4 14B?

No. Phi-4 14B needs ~10.8 GB even at Q4_K_M, but iPhone 16 Pro only has ~4.5 GB usable.

How much memory does Phi-4 14B need?

iPhone 16 Pro does not have enough memory. At Q4_K_M the weights are ~9.05 GB; with KV cache and runtime overhead, budget ~10.8 GB at a 4k context.

What is the best tool to run Phi-4 14B on iOS?

On iPhone and iPad, Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.) is the standard choice. Phones realistically run 1B-4B class models. Anything larger thermally throttles or OOMs.

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Markdown

[![Phi-4 14B on iPhone 16 Pro](https://localmodel.run/badge/phi-4-14b/iphone-16-pro.svg)](https://localmodel.run/can-i-run/phi-4-14b/iphone-16-pro)

Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.