Run Gemma 4 on iPhone 16 Pro with Google AI Edge Gallery

iPhone 16 Pro is the first iPhone with confirmed real-world Gemma 4 benchmarks. A Hacker News user running the April 2026 build of Google AI Edge Gallery measured Gemma 4 E2B at 30 tokens per second on the A18 Pro chip with 8 GB of RAM. That puts it within striking distance of a Galaxy S25 Edge and well ahead of older iPhones. The catch: sustained generation gets the device hot. For everyday chat, translation, and image Q&A it is excellent.

Apple A18 Pro8 GB RAM2024

Quick answer

On the iPhone 16 Pro (Apple A18 Pro, 8GB RAM), run Google Gemma 4 E2B at ~30 tok/s (measured) via Google AI Edge Gallery. Gemma 4 E2B is ~2.5 GB on disk and uses 1-1.5 GB in memory, fully offline, no account required.

Sizing rule: an on-device model must fit its weights plus working memory inside the iPhone 16 Pro's 8GB of RAM, shared with iOS and the host app. The larger Gemma 4 E4B (~5GB on disk, 2-3GB in use) is the quality upgrade, but it only fits phones with more free memory. Everything runs fully offline once the model is downloaded, and speed varies with thermal state during long sessions. What it will not run: 7B-class and larger models exceed a phone's usable memory; those need a Mac, a GPU, or a cloud API.

→ Install Google AI Edge Gallery (iOS 17+), then download Gemma 4.

TOP PICK

Gemma 4 E2B

SPEED

~30 tok/s (measured)

DEVICE RAM

8 GB

Speed is a real-world user-reported measurement; on-device speed varies with thermal state.

Cite this page: ModelFit, Run Gemma 4 on iPhone 16 Pro: 30 tok/s Confirmed (2026), https://modelfit.io/iphone/iphone-16-pro/, updated August 2026, CC BY 4.0.

Last updated: August 26, 2026 · Editor: ModelFit Team

Verdict

Recommended: Gemma 4 E2B

iPhone 16 Pro hits 30 tok/s on Gemma 4 E2B in real-world testing. The fastest non-Pro-Max iPhone for on-device AI.

Hardware Profile

DEVICE

iPhone 16 Pro

CHIP

Apple A18 Pro

RAM

8 GB

NEURAL ENGINE

16-core

Gemma 4 Performance on iPhone 16 Pro

Bar chart: Gemma 4 speed on iPhone 16 Pro in Google AI Edge Gallery. Gemma 4 E2B ~30 tok/s, Gemma 4 E4B ~15 tok/s.

Model	Download	RAM in Use	Speed	Source
Gemma 4 E2BTop Pick	~2.5 GB	1-1.5 GB	~30 tok/s	Measured
Gemma 4 E4B	~5 GB	2-3 GB	~15 tok/s	Estimated

Speeds via Google AI Edge Gallery on iOS 17+. "Measured" numbers come from real-world Hacker News user reports; "Estimated" numbers are interpolations from chip generation. Both Gemma 4 variants use int4 quantization-aware training.

Best for

Confirmed fastest 8 GB iPhone for Gemma 4 E2B
Multimodal: photograph anything and ask Gemma about it
Offline use during travel and on flights
Privacy-sensitive personal use cases

Watch outs

Sustained inference triggers thermal throttling. The device gets noticeably hot
E4B borderline on 8 GB. Works but pressures memory
Battery drain ~15-20% per hour of continuous chat

Setup Guide

Step-by-step install for Google AI Edge Gallery on iPhone 16 Pro, plus full benchmarks and the privacy details.

Read the full guide

Frequently Asked Questions

How fast is Gemma 4 on iPhone 16 Pro?

Real-world: roughly 30 tokens per second for Gemma 4 E2B, per a Hacker News user report from April 2026 (news.ycombinator.com, item 47652561). That same user noted the phone got considerably warm during extended generation, which is normal under sustained load on the A18 Pro.

Does iPhone 16 Pro get hot when running Gemma?

Yes, under sustained load. Quick prompts and short conversations stay cool. Long reasoning chains, batch document analysis, or back-to-back image Q&A push the A18 Pro hard enough to trigger thermal management. Take breaks during heavy use or run shorter prompts.

Can iPhone 16 Pro run Gemma 4 E4B?

Technically yes, but it is borderline on 8 GB of RAM. E4B uses 2-3 GB during inference and ~5 GB on disk. iOS will aggressively evict background apps. Expect ~15 tok/s and watch for slowdowns when memory is tight. For E4B comfort, iPhone 17 Pro with 12 GB RAM is the better target.

Is iPhone 16 Pro better than iPhone 15 Pro for local AI?

Yes, by roughly 30-40%. The A18 Pro is faster than the A17 Pro at the same workload, both on CPU and on the Neural Engine. Both have 8 GB RAM, so the model selection is identical, but iPhone 16 Pro generates tokens noticeably faster and runs cooler under sustained load.