text model · Qwen2.5 · Android

Can I run Qwen2.5 32B on Samsung Galaxy S25 Ultra (16GB, 1TB config only)?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Qwen2.5 32B needs ~22.1 GB even at Q4_K_M, but Samsung Galaxy S25 Ultra (16GB, 1TB config only) only has ~12 GB usable.

Needs ~22.1 GB Device usable ~12 GB

Needs ~22.1 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 10.1 GB: Qwen2.5 32B needs roughly 22.1 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 Qwen2.5 32B is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Qwen2.5 32B on Nvidia GeForce RTX 4090 (24GB).

Q4_K_M needed: ~22.1 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

~15.6 GB

Q3_K_M

~17.8 GB

Q4_K_M

~22.1 GB

Q5_K_M

~25 GB

Q6_K

~28.4 GB

Q8_0

~37 GB

FP16

~66.2 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 Qwen2.5

Parameters: 32B
Q4_K_M size: 19.85 GB
Q8_0 size: 34.82 GB
Context: 128k
Ollama tag: qwen2.5:32b

Full Qwen2.5 32B 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 Qwen2.5 32B on other hardware

Nvidia GeForce RTX 4090 (24GB)Nvidia GeForce RTX 3090 (24GB)AMD Radeon RX 7900 XTX (24GB)Nvidia GeForce RTX 5090 (32GB)32GB RAM Laptop (CPU/iGPU only)Apple M4 Pro (48GB)

FAQ

Can Samsung Galaxy S25 Ultra (16GB, 1TB config only) run Qwen2.5 32B?

No. Qwen2.5 32B needs ~22.1 GB even at Q4_K_M, but Samsung Galaxy S25 Ultra (16GB, 1TB config only) only has ~12 GB usable.

How much memory does Qwen2.5 32B need?

Samsung Galaxy S25 Ultra (16GB, 1TB config only) does not have enough memory. At Q4_K_M the weights are ~19.85 GB; with KV cache and runtime overhead, budget ~22.1 GB at a 4k context.

What is the best tool to run Qwen2.5 32B 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

[![Qwen2.5 32B on Samsung Galaxy S25 Ultra (16GB, 1TB config only)](https://localmodel.run/badge/qwen2.5-32b/samsung-s25-ultra-16gb.svg)](https://localmodel.run/can-i-run/qwen2.5-32b/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.