text model · llama · Android
Can I run Llama 3.3 70B on Samsung Galaxy S25 Ultra (16GB, 1TB config only)?
No. Llama 3.3 70B needs ~45.3 GB even at Q4_K_M, but Samsung Galaxy S25 Ultra (16GB, 1TB config only) only has ~12 GB usable.
Needs ~45.3 GB even at Q4_K_M, but only ~12 GB is usable.
- Q4_K_M needed
- ~45.3 GB
- Usable on device
- ~12 GB
- Device memory
- 16 GB
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
- 70B
- Q4_K_M size
- 42.52 GB
- Q8_0 size
- 74.98 GB
- Context
- 128k
- Ollama tag
- llama3.3:70b
- Memory
- 16 GB ram
- Usable for weights
- ~12 GB
- Best runtime
- llama.cpp (PocketPal) or MLC-LLM (Adreno GPU path)
What you can run instead
Run Llama 3.3 70B on other hardware
FAQ
Can Samsung Galaxy S25 Ultra (16GB, 1TB config only) run Llama 3.3 70B?
No. Llama 3.3 70B needs ~45.3 GB even at Q4_K_M, but Samsung Galaxy S25 Ultra (16GB, 1TB config only) only has ~12 GB usable.
How much memory does Llama 3.3 70B need?
Samsung Galaxy S25 Ultra (16GB, 1TB config only) does not have enough memory. At Q4_K_M the weights are ~42.52 GB; with KV cache and runtime overhead, budget ~45.3 GB at a 4k context.
What is the best tool to run Llama 3.3 70B 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.