text model · Gemma · iOS

Can I run Gemma 2 27B on iPhone 16 Pro?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Gemma 2 27B needs ~18.7 GB even at Q4_K_M, but iPhone 16 Pro only has ~4.5 GB usable.

Needs ~18.7 GB Device usable ~4.5 GB

Needs ~18.7 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 14.2 GB: Gemma 2 27B needs roughly 18.7 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 Gemma 2 27B is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Gemma 2 27B on Nvidia GeForce RTX 4090 (24GB).

Q4_K_M needed: ~18.7 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

~13.3 GB

Q3_K_M

~15.2 GB

Q4_K_M

~18.7 GB

Q5_K_M

~21.2 GB

Q6_K

~24.1 GB

Q8_0

~30.9 GB

FP16

~56 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 Gemma

Parameters: 27B
Q4_K_M size: 16.65 GB
Q8_0 size: 28.94 GB
Context: 8k
Ollama tag: gemma2:27b

Full Gemma 2 27B 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 Gemma 2 27B on other hardware

Nvidia GeForce RTX 4090 (24GB)Nvidia GeForce RTX 3090 (24GB)AMD Radeon RX 7900 XTX (24GB)Nvidia GeForce RTX 5090 (32GB)32GB RAM Laptop (CPU/iGPU only)Apple M5 (32GB)

FAQ

Can iPhone 16 Pro run Gemma 2 27B?

No. Gemma 2 27B needs ~18.7 GB even at Q4_K_M, but iPhone 16 Pro only has ~4.5 GB usable.

How much memory does Gemma 2 27B need?

iPhone 16 Pro does not have enough memory. At Q4_K_M the weights are ~16.65 GB; with KV cache and runtime overhead, budget ~18.7 GB at a 4k context.

What is the best tool to run Gemma 2 27B 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 27B on iPhone 16 Pro](https://localmodel.run/badge/gemma-2-27b/iphone-16-pro.svg)](https://localmodel.run/can-i-run/gemma-2-27b/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.