text model · Qwen3 · Android
Can I run Qwen3 32B on Samsung Galaxy S26 Ultra (16GB, 1TB config)?
No. Qwen3 32B needs ~22 GB even at Q4_K_M, but Samsung Galaxy S26 Ultra (16GB, 1TB config) only has ~12 GB usable.
Needs ~22 GB even at Q4_K_M, but only ~12 GB is usable.
- Q4_K_M needed
- ~22 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
- 32B
- Q4_K_M size
- 19.8 GB
- Q8_0 size
- 34.8 GB
- Context
- 32k
- Ollama tag
- qwen3:32b
- 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 Qwen3 32B on other hardware
FAQ
Can Samsung Galaxy S26 Ultra (16GB, 1TB config) run Qwen3 32B?
No. Qwen3 32B needs ~22 GB even at Q4_K_M, but Samsung Galaxy S26 Ultra (16GB, 1TB config) only has ~12 GB usable.
How much memory does Qwen3 32B need?
Samsung Galaxy S26 Ultra (16GB, 1TB config) does not have enough memory. At Q4_K_M the weights are ~19.8 GB; with KV cache and runtime overhead, budget ~22 GB at a 4k context.
What is the best tool to run Qwen3 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.
Sources
Memory figures are estimates. See methodology.