text model · EXAONE · Android
Can I run EXAONE 4.0 32B on Google Pixel 9 Pro?
No. EXAONE 4.0 32B needs ~20.2 GB even at Q4_K_M, but Google Pixel 9 Pro only has ~10.5 GB usable.
Needs ~20.2 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 9.7 GB: EXAONE 4.0 32B needs roughly 20.2 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 EXAONE 4.0 32B is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See EXAONE 4.0 32B on Nvidia GeForce RTX 4090 (24GB).
- Q4_K_M needed
- ~20.2 GB
- Usable on device
- ~10.5 GB
- Device memory
- 16 GB
Which quant fits
How to run it
On Android use PocketPal AI (Polished app, download GGUF and run offline.).
- Parameters
- 32B
- Q4_K_M size
- 18.02 GB
- Q8_0 size
- 31.67 GB
- Context
- 131k
- Memory
- 16 GB ram
- Usable for weights
- ~10.5 GB
- Best runtime
- llama.cpp (PocketPal) or MLC-LLM (Adreno GPU path)
What you can run instead
Run EXAONE 4.0 32B on other hardware
FAQ
Can Google Pixel 9 Pro run EXAONE 4.0 32B?
No. EXAONE 4.0 32B needs ~20.2 GB even at Q4_K_M, but Google Pixel 9 Pro only has ~10.5 GB usable.
How much memory does EXAONE 4.0 32B need?
Google Pixel 9 Pro does not have enough memory. At Q4_K_M the weights are ~18.02 GB; with KV cache and runtime overhead, budget ~20.2 GB at a 4k context.
What is the best tool to run EXAONE 4.0 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.
Embed this
A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/exaone-4-32b/pixel-9-pro) Sources
-
9to5google.com · 1 source
-
androidpolice.com · 1 source
-
comparigon.com · 1 source
-
github.com · 5 sources
-
gsmarena.com · 2 sources
-
huggingface.co · 3 sources
-
layla-network.ai · 1 source
-
mlc.ai · 1 source
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.