text model · Nemotron · Android

Can I run Llama-3.3-Nemotron-Super-49B-v1 on Samsung Galaxy S25 Ultra (16GB, 1TB config only)?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Llama-3.3-Nemotron-Super-49B-v1 needs ~30.6 GB even at Q4_K_M, but Samsung Galaxy S25 Ultra (16GB, 1TB config only) only has ~12 GB usable.

Needs ~30.6 GB Device usable ~12 GB

Needs ~30.6 GB even at Q4_K_M, but only ~12 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 18.6 GB: Llama-3.3-Nemotron-Super-49B-v1 needs roughly 30.6 GB at Q4_K_M and Samsung Galaxy S25 Ultra (16GB, 1TB config only) leaves only about 12 GB usable for a model. The lightest tracked hardware that runs Llama-3.3-Nemotron-Super-49B-v1 is the Nvidia GeForce RTX 5090 (32GB) at 32 GB. See Llama-3.3-Nemotron-Super-49B-v1 on Nvidia GeForce RTX 5090 (32GB).

Q4_K_M needed: ~30.6 GB
Usable on device: ~12 GB
Device memory: 16 GB

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Which quant fits

Quant ladder vs ~12 GB usable

Q2_K

~23 GB

Q3_K_M

~26.4 GB

Q4_K_M

~30.6 GB

Q5_K_M

~37.4 GB

Q6_K

~42.7 GB

Q8_0

~51.9 GB

FP16

~102.2 GB

The line marks Samsung Galaxy S25 Ultra (16GB, 1TB config only)'s ~12 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

Parameters: 49B
Q4_K_M size: 28.14 GB
Q8_0 size: 49.36 GB
Context: 128k

Full Llama-3.3-Nemotron-Super-49B-v1 requirements →

Device Android

Memory: 16 GB ram
Usable for weights: ~12 GB
Power draw: ~8 W
Best runtime: llama.cpp (PocketPal) or MLC-LLM (Adreno GPU path)

Best models for Samsung Galaxy S25 Ultra (16GB, 1TB config only) →

What you can run instead

Run Llama-3.3-Nemotron-Super-49B-v1 on other hardware

Nvidia GeForce RTX 5090 (32GB)Apple M4 Pro (48GB)Apple M5 Pro (48GB)Apple M4 Max (64GB)Apple M4 Max (128GB)AMD Ryzen AI Halo (128GB)

FAQ

Can Samsung Galaxy S25 Ultra (16GB, 1TB config only) run Llama-3.3-Nemotron-Super-49B-v1?

No. Llama-3.3-Nemotron-Super-49B-v1 needs ~30.6 GB even at Q4_K_M, but Samsung Galaxy S25 Ultra (16GB, 1TB config only) only has ~12 GB usable.

How much memory does Llama-3.3-Nemotron-Super-49B-v1 need?

Samsung Galaxy S25 Ultra (16GB, 1TB config only) does not have enough memory. At Q4_K_M the weights are ~28.14 GB; with KV cache and runtime overhead, budget ~30.6 GB at a 4k context.

What is the best tool to run Llama-3.3-Nemotron-Super-49B-v1 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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Markdown

[![Llama-3.3-Nemotron-Super-49B-v1 on Samsung Galaxy S25 Ultra (16GB, 1TB config only)](https://localmodel.run/badge/nemotron-super-49b/samsung-s25-ultra-16gb.svg)](https://localmodel.run/can-i-run/nemotron-super-49b/samsung-s25-ultra-16gb)

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.