text model · llama · Android
Can I run Llama 3.2 1B on Samsung Galaxy S25 Ultra (16GB, 1TB config only)?
Yes. Llama 3.2 1B runs on Samsung Galaxy S25 Ultra (16GB, 1TB config only) at Q4_K_M (~1.8 GB of ~12 GB usable).
Runs at Q4_K_M using ~1.8 GB of ~12 GB usable. You have room for FP16 for higher quality.
- Q4_K_M needed
- ~1.8 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
- 1B
- Q4_K_M size
- 0.81 GB
- Q8_0 size
- 1.32 GB
- Context
- 128k
- Ollama tag
- llama3.2:1b
- 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 Llama 3.2 1B on other hardware
FAQ
Can Samsung Galaxy S25 Ultra (16GB, 1TB config only) run Llama 3.2 1B?
Yes. Llama 3.2 1B runs on Samsung Galaxy S25 Ultra (16GB, 1TB config only) at Q4_K_M (~1.8 GB of ~12 GB usable).
How much memory does Llama 3.2 1B need?
Samsung Galaxy S25 Ultra (16GB, 1TB config only) has room to spare. At Q4_K_M the weights are ~0.81 GB; with KV cache and runtime overhead, budget ~1.8 GB at a 4k context.
What is the best tool to run Llama 3.2 1B 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.