text model · Qwen2.5-VL · Android
Can I run Qwen2.5-VL 7B on Samsung Galaxy S26 Ultra (16GB, 1TB config)?
Yes. Qwen2.5-VL 7B runs on Samsung Galaxy S26 Ultra (16GB, 1TB config) at Q4_K_M (~7.1 GB of ~12 GB usable).
Runs at Q4_K_M using ~7.1 GB of ~12 GB usable. You have room for Q8_0 for higher quality.
- Q4_K_M needed
- ~7.1 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
- 8.29B
- Q4_K_M size
- 5.62 GB
- Q8_0 size
- 9.59 GB
- Context
- 32k
- 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 Qwen2.5-VL 7B on other hardware
FAQ
Can Samsung Galaxy S26 Ultra (16GB, 1TB config) run Qwen2.5-VL 7B?
Yes. Qwen2.5-VL 7B runs on Samsung Galaxy S26 Ultra (16GB, 1TB config) at Q4_K_M (~7.1 GB of ~12 GB usable).
How much memory does Qwen2.5-VL 7B need?
Samsung Galaxy S26 Ultra (16GB, 1TB config) has room to spare. At Q4_K_M the weights are ~5.62 GB; with KV cache and runtime overhead, budget ~7.1 GB at a 4k context.
What is the best tool to run Qwen2.5-VL 7B 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.