text model · Gemma · Android
Can I run Gemma 4 E4B on Google Pixel 10 Pro?
Yes. Gemma 4 E4B runs on Google Pixel 10 Pro at Q4_K_M (~6.5 GB of ~10.5 GB usable).
Runs at Q4_K_M using ~6.5 GB of ~10.5 GB usable. You have room for Q8_0 for higher quality.
That figure is at a 4k context and moves about ±15% as context length changes. Google Pixel 10 Pro leaves ~4 GB of headroom, room to step up to Q8_0 for higher quality.
- Q4_K_M needed
- ~6.5 GB
- Usable on device
- ~10.5 GB
- Device memory
- 16 GB
- Best quant
- Q4_K_M
Which quant fits
Running cost · estimate
- Power draw
- ~7 W
- Electricity / 1M tokens
- ~$0.04
- Pays for itself after
- ~2,172M tok
At ~$0.15/kWh and the estimated ~7 tok/s, a million generated tokens costs about $0.04 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$999 Google Pixel 10 Pro pays for itself after roughly 2,172 million tokens, so local hardware is mostly a fixed cost, not a per-token one. TDP is the peak draw, so this is an upper bound. Assumptions.
How to run it
On Android use PocketPal AI (Polished app, download GGUF and run offline.).
- Parameters
- 8B
- Q4_K_M size
- 4.98 GB
- Q8_0 size
- 8.19 GB
- Context
- 128k
- Ollama tag
- gemma4:e4b
- 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)
You could also run
Run Gemma 4 E4B on other hardware
FAQ
Can Google Pixel 10 Pro run Gemma 4 E4B?
Yes. Gemma 4 E4B runs on Google Pixel 10 Pro at Q4_K_M (~6.5 GB of ~10.5 GB usable).
How much memory does Gemma 4 E4B need?
Google Pixel 10 Pro has room to spare. At Q4_K_M the weights are ~4.98 GB; with KV cache and runtime overhead, budget ~6.5 GB at a 4k context.
What is the best tool to run Gemma 4 E4B 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
[](https://localmodel.run/can-i-run/gemma-4-e4b/pixel-10-pro) Sources
- 9to5google.com
- gadgetversus.com
- github.com/a-ghorbani
- github.com/google-ai-edge
- github.com/mlc-ai
- github.com/shubham0204
- github.com/Vali-98
- gsmarena.com
- huggingface.co/google
- huggingface.co/unsloth
- layla-network.ai
- ollama.com
- store.google.com/product/pixel_10_pro
- store.google.com/product/pixel_10_pro_specs
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.