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text model · Nemotron 3 · Android

Can I run Nemotron 3 Super 120B-A12B on Generic Android Phone (8GB RAM)?

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

No. Nemotron 3 Super 120B-A12B needs ~80.3 GB even at Q4_K_M, but Generic Android Phone (8GB RAM) only has ~4.5 GB usable.

Needs ~80.3 GB Device usable ~4.5 GB

Needs ~80.3 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 75.8 GB: Nemotron 3 Super 120B-A12B needs roughly 80.3 GB at Q4_K_M and Generic Android Phone (8GB RAM) leaves only about 4.5 GB usable for a model. The lightest tracked hardware that runs Nemotron 3 Super 120B-A12B is the Apple M4 Max (128GB) at 128 GB. See Nemotron 3 Super 120B-A12B on Apple M4 Max (128GB).

Q4_K_M needed
~80.3 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
~53.7 GB
Q3_K_M
~62.1 GB
Q4_K_M
~80.3 GB
Q5_K_M
~88.9 GB
Q6_K
~101.8 GB
Q8_0
~123.1 GB
FP16
~228.3 GB
The line marks Generic Android Phone (8GB RAM)'s ~4.5 GB budget; rungs past it are too large.

How to run it

On Android use PocketPal AI (Polished app, download GGUF and run offline.).

Model Nemotron 3
Parameters
120B (MoE, 12B active)
Q4_K_M size
76.87 GB
Q8_0 size
119.65 GB
Context
256k
Ollama tag
nemotron-3-super:120b-a12b
Full Nemotron 3 Super 120B-A12B requirements →
Device Android
Memory
8 GB ram
Usable for weights
~4.5 GB
Best runtime
llama.cpp (PocketPal or SmolChat)
Best models for Generic Android Phone (8GB RAM) →

What you can run instead

Run Nemotron 3 Super 120B-A12B on other hardware

FAQ

Can Generic Android Phone (8GB RAM) run Nemotron 3 Super 120B-A12B?

No. Nemotron 3 Super 120B-A12B needs ~80.3 GB even at Q4_K_M, but Generic Android Phone (8GB RAM) only has ~4.5 GB usable.

How much memory does Nemotron 3 Super 120B-A12B need?

Generic Android Phone (8GB RAM) does not have enough memory. At Q4_K_M the weights are ~76.87 GB; with KV cache and runtime overhead, budget ~80.3 GB at a 4k context. It is a Mixture-of-Experts model (120B total / 12B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run Nemotron 3 Super 120B-A12B on Android?

On Android, PocketPal AI (Polished app, download GGUF and run offline.) is the go-to option. NPU acceleration is limited and chip-specific; most apps run on CPU. Expect 1B-4B class.

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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.