text model · OLMo · Android

Can I run OLMo 2 32B Instruct on Google Pixel 9 Pro?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. OLMo 2 32B Instruct needs ~21.7 GB even at Q4_K_M, but Google Pixel 9 Pro only has ~10.5 GB usable.

Needs ~21.7 GB Device usable ~10.5 GB

Needs ~21.7 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 11.2 GB: OLMo 2 32B Instruct needs roughly 21.7 GB at Q4_K_M and Google Pixel 9 Pro leaves only about 10.5 GB usable for a model. The lightest tracked hardware that runs OLMo 2 32B Instruct is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See OLMo 2 32B Instruct on Nvidia GeForce RTX 4090 (24GB).

Q4_K_M needed: ~21.7 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

~15.6 GB

Q3_K_M

~17.8 GB

Q4_K_M

~21.7 GB

Q5_K_M

~25 GB

Q6_K

~28.4 GB

Q8_0

~36.5 GB

FP16

~66.7 GB

The line marks Google Pixel 9 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 OLMo

Parameters: 32B
Q4_K_M size: 19.5 GB
Q8_0 size: 34.3 GB
Context: 4k

Full OLMo 2 32B Instruct requirements →

Device Android

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

Best models for Google Pixel 9 Pro →

What you can run instead

Run OLMo 2 32B Instruct 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 Google Pixel 9 Pro run OLMo 2 32B Instruct?

No. OLMo 2 32B Instruct needs ~21.7 GB even at Q4_K_M, but Google Pixel 9 Pro only has ~10.5 GB usable.

How much memory does OLMo 2 32B Instruct need?

Google Pixel 9 Pro does not have enough memory. At Q4_K_M the weights are ~19.5 GB; with KV cache and runtime overhead, budget ~21.7 GB at a 4k context.

What is the best tool to run OLMo 2 32B Instruct 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

[![OLMo 2 32B Instruct on Google Pixel 9 Pro](https://localmodel.run/badge/olmo-2-32b/pixel-9-pro.svg)](https://localmodel.run/can-i-run/olmo-2-32b/pixel-9-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.