text model · Qwen3 · Android

Can I run Qwen3 14B on Google Pixel 10 Pro?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Qwen3 14B needs ~10.7 GB even at Q4_K_M, but Google Pixel 10 Pro only has ~10.5 GB usable.

Needs ~10.7 GB Device usable ~10.5 GB

Needs ~10.7 GB even at Q4_K_M, but only ~10.5 GB is usable.

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

The gap is about 0.2 GB: Qwen3 14B needs roughly 10.7 GB at Q4_K_M and Google Pixel 10 Pro leaves only about 10.5 GB usable for a model. The lightest tracked hardware that runs Qwen3 14B is the Nvidia GeForce RTX 3060 (12GB) at 12 GB. See Qwen3 14B on Nvidia GeForce RTX 3060 (12GB).

Q4_K_M needed: ~10.7 GB
Usable on device: ~10.5 GB
Device memory: 16 GB

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Which quant fits

Quant ladder vs ~10.5 GB usable

Q2_K

~7.6 GB

Q3_K_M

~8.5 GB

Q4_K_M

~10.7 GB

Q5_K_M

~11.7 GB

Q6_K

~13.2 GB

Q8_0

~17.4 GB

FP16

~31.7 GB

The line marks Google Pixel 10 Pro's ~10.5 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 Qwen3

Parameters: 14B
Q4_K_M size: 9 GB
Q8_0 size: 15.7 GB
Context: 32k
Ollama tag: qwen3:14b

Full Qwen3 14B requirements →

Device Android

Memory: 16 GB ram
Usable for weights: ~10.5 GB
Power draw: ~7 W
Best runtime: llama.cpp (PocketPal) or MLC-LLM (Adreno GPU path)

Best models for Google Pixel 10 Pro →

What you can run instead

Run Qwen3 14B on other hardware

Nvidia GeForce RTX 3060 (12GB)Nvidia GeForce RTX 4070 (12GB)Nvidia GeForce RTX 4060 Ti (16GB)Nvidia GeForce RTX 4080 (16GB)16GB RAM Laptop (CPU/iGPU only)iPad Pro M4 (16GB, 1TB/2TB config)

FAQ

Can Google Pixel 10 Pro run Qwen3 14B?

No. Qwen3 14B needs ~10.7 GB even at Q4_K_M, but Google Pixel 10 Pro only has ~10.5 GB usable.

How much memory does Qwen3 14B need?

Google Pixel 10 Pro does not have enough memory. At Q4_K_M the weights are ~9 GB; with KV cache and runtime overhead, budget ~10.7 GB at a 4k context.

What is the best tool to run Qwen3 14B 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

[![Qwen3 14B on Google Pixel 10 Pro](https://localmodel.run/badge/qwen3-14b/pixel-10-pro.svg)](https://localmodel.run/can-i-run/qwen3-14b/pixel-10-pro)

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.