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Can I run Nemotron 3.5 Bolt E4B on iPhone 16 Pro?

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

No. Nemotron 3.5 Bolt E4B needs ~8.9 GB even at Q4_K_M, but iPhone 16 Pro only has ~4.5 GB usable.

Needs ~8.9 GB Device usable ~4.5 GB

Needs ~8.9 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 4.4 GB: Nemotron 3.5 Bolt E4B needs roughly 8.9 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 Nemotron 3.5 Bolt E4B is the Nvidia GeForce RTX 3060 (12GB) at 12 GB. See Nemotron 3.5 Bolt E4B on Nvidia GeForce RTX 3060 (12GB).

Q4_K_M needed
~8.9 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
~4.9 GB
Q3_K_M
~5.4 GB
Q4_K_M
~8.9 GB
Q5_K_M
~7.2 GB
Q6_K
~8.1 GB
Q8_0
~10.6 GB
FP16
~17.1 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
Parameters
8B
Q4_K_M size
7.37 GB
Q8_0 size
9.09 GB
Context
64k
Ollama tag
nemotron-3.5-bolt:e4b-q4_K_M
Full Nemotron 3.5 Bolt E4B 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 Nemotron 3.5 Bolt E4B on other hardware

FAQ

Can iPhone 16 Pro run Nemotron 3.5 Bolt E4B?

No. Nemotron 3.5 Bolt E4B needs ~8.9 GB even at Q4_K_M, but iPhone 16 Pro only has ~4.5 GB usable.

How much memory does Nemotron 3.5 Bolt E4B need?

iPhone 16 Pro does not have enough memory. At Q4_K_M the weights are ~7.37 GB; with KV cache and runtime overhead, budget ~8.9 GB at a 4k context.

What is the best tool to run Nemotron 3.5 Bolt E4B 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.