text model · Llama 4 · Android

Can I run Llama 4 Maverick on Samsung Galaxy S25 Ultra (16GB, 1TB config only)?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Llama 4 Maverick needs ~231.7 GB even at Q4_K_M, but Samsung Galaxy S25 Ultra (16GB, 1TB config only) only has ~12 GB usable.

Needs ~231.7 GB Device usable ~12 GB

Needs ~231.7 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 219.7 GB: Llama 4 Maverick needs roughly 231.7 GB at Q4_K_M and Samsung Galaxy S25 Ultra (16GB, 1TB config only) leaves only about 12 GB usable for a model. No single tracked device has enough memory; Llama 4 Maverick needs a multi-GPU or high-memory rig.

Q4_K_M needed: ~231.7 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

~173.1 GB

Q3_K_M

~201.1 GB

Q4_K_M

~231.7 GB

Q5_K_M

~290.6 GB

Q6_K

~333.6 GB

Q8_0

~402.2 GB

FP16

~806.6 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 Llama 4

Parameters: 400B (MoE, 17B active)
Q4_K_M size: 226.09 GB
Q8_0 size: 396.57 GB
Context: 1000k
Ollama tag: llama4:128x17b

Full Llama 4 Maverick 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

FAQ

Can Samsung Galaxy S25 Ultra (16GB, 1TB config only) run Llama 4 Maverick?

No. Llama 4 Maverick needs ~231.7 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 4 Maverick need?

Samsung Galaxy S25 Ultra (16GB, 1TB config only) does not have enough memory. At Q4_K_M the weights are ~226.09 GB; with KV cache and runtime overhead, budget ~231.7 GB at a 4k context. It is a Mixture-of-Experts model (400B total / 17B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run Llama 4 Maverick 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 4 Maverick on Samsung Galaxy S25 Ultra (16GB, 1TB config only)](https://localmodel.run/badge/llama-4-maverick/samsung-s25-ultra-16gb.svg)](https://localmodel.run/can-i-run/llama-4-maverick/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.