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text model · Nemotron 3 · iOS

Can I run Nemotron 3 Ultra 550B-A55B on iPhone 16 Pro?

Compatibility verdict VRAM threshold engine
No, not enough memory would not load

No. Nemotron 3 Ultra 550B-A55B needs ~341 GB even at Q4_K_M, but iPhone 16 Pro only has ~4.5 GB usable.

Needs ~341 GB Device usable ~4.5 GB

Needs ~341 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 336.5 GB: Nemotron 3 Ultra 550B-A55B needs roughly 341 GB at Q4_K_M and iPhone 16 Pro leaves only about 4.5 GB usable for a model. No single tracked device has enough memory; Nemotron 3 Ultra 550B-A55B needs a multi-GPU or high-memory rig.

Q4_K_M needed
~341 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
~236.7 GB
Q3_K_M
~275.2 GB
Q4_K_M
~341 GB
Q5_K_M
~398.3 GB
Q6_K
~457.4 GB
Q8_0
~550.5 GB
FP16
~1106.4 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 Nemotron 3
Parameters
550B (MoE, 55B active)
Q4_K_M size
334.55 GB
Q8_0 size
544.13 GB
Context
256k
Full Nemotron 3 Ultra 550B-A55B 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

FAQ

Can iPhone 16 Pro run Nemotron 3 Ultra 550B-A55B?

No. Nemotron 3 Ultra 550B-A55B needs ~341 GB even at Q4_K_M, but iPhone 16 Pro only has ~4.5 GB usable.

How much memory does Nemotron 3 Ultra 550B-A55B need?

iPhone 16 Pro does not have enough memory. At Q4_K_M the weights are ~334.55 GB; with KV cache and runtime overhead, budget ~341 GB at a 4k context. It is a Mixture-of-Experts model (550B total / 55B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run Nemotron 3 Ultra 550B-A55B 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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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.