text model · gemma · Android
Can I run Gemma 3 12B on Samsung Galaxy S26 Ultra (16GB, 1TB config)?
Yes. Gemma 3 12B runs on Samsung Galaxy S26 Ultra (16GB, 1TB config) at Q4_K_M (~8.9 GB of ~12 GB usable).
Runs at Q4_K_M using ~8.9 GB of ~12 GB usable.
- Q4_K_M needed
- ~8.9 GB
- Usable on device
- ~12 GB
- Device memory
- 16 GB
- Best quant
- Q4_K_M
How to run it
On Android use PocketPal AI (Polished app, download GGUF and run offline.). NPU acceleration is limited and chip-specific; most apps run on CPU. Expect 1B-4B class.
- Parameters
- 12B
- Q4_K_M size
- 7.3 GB
- Q8_0 size
- 12.51 GB
- Context
- 128k
- Ollama tag
- gemma3:12b
- Memory
- 16 GB ram
- Usable for weights
- ~12 GB
- Best runtime
- llama.cpp (PocketPal) or MLC-LLM (Adreno GPU path)
You could also run
Run Gemma 3 12B on other hardware
FAQ
Can Samsung Galaxy S26 Ultra (16GB, 1TB config) run Gemma 3 12B?
Yes. Gemma 3 12B runs on Samsung Galaxy S26 Ultra (16GB, 1TB config) at Q4_K_M (~8.9 GB of ~12 GB usable).
How much memory does Gemma 3 12B need?
Samsung Galaxy S26 Ultra (16GB, 1TB config) has room to spare. At Q4_K_M the weights are ~7.3 GB; with KV cache and runtime overhead, budget ~8.9 GB at a 4k context.
What is the best tool to run Gemma 3 12B 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.
Sources
Memory figures are estimates. See methodology.