text model · Gemma · iOS

Can I run Gemma 2 9B on iPhone 15 Pro?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Gemma 2 9B needs ~7.3 GB even at Q4_K_M, but iPhone 15 Pro only has ~4.5 GB usable.

Needs ~7.3 GB Device usable ~4.5 GB

Needs ~7.3 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 2.8 GB: Gemma 2 9B needs roughly 7.3 GB at Q4_K_M and iPhone 15 Pro leaves only about 4.5 GB usable for a model. The lightest tracked hardware that runs Gemma 2 9B is the Nvidia GeForce RTX 3060 (12GB) at 12 GB. See Gemma 2 9B on Nvidia GeForce RTX 3060 (12GB).

Q4_K_M needed: ~7.3 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

~5.3 GB

Q3_K_M

~5.9 GB

Q4_K_M

~7.3 GB

Q5_K_M

~7.9 GB

Q6_K

~8.9 GB

Q8_0

~11.3 GB

FP16

~19.5 GB

The line marks iPhone 15 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 Gemma

Parameters: 9B
Q4_K_M size: 5.76 GB
Q8_0 size: 9.83 GB
Context: 8k
Ollama tag: gemma2:9b

Full Gemma 2 9B requirements →

Device iOS

Memory: 8 GB unified
Usable for weights: ~4.5 GB
Power draw: ~14 W
Best runtime: llama.cpp + Metal (via PocketPal or Off Grid app)

Best models for iPhone 15 Pro →

What you can run instead

Run Gemma 2 9B on other hardware

Nvidia GeForce RTX 3060 (12GB)Nvidia GeForce RTX 4070 (12GB)Samsung Galaxy S24 Ultra Generic Android Phone (12GB RAM)iPhone 17 Pro iPhone Air

FAQ

Can iPhone 15 Pro run Gemma 2 9B?

No. Gemma 2 9B needs ~7.3 GB even at Q4_K_M, but iPhone 15 Pro only has ~4.5 GB usable.

How much memory does Gemma 2 9B need?

iPhone 15 Pro does not have enough memory. At Q4_K_M the weights are ~5.76 GB; with KV cache and runtime overhead, budget ~7.3 GB at a 4k context.

What is the best tool to run Gemma 2 9B 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

[![Gemma 2 9B on iPhone 15 Pro](https://localmodel.run/badge/gemma-2-9b/iphone-15-pro.svg)](https://localmodel.run/can-i-run/gemma-2-9b/iphone-15-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.