text model · Qwen2.5-VL · Android
Can I run Qwen2.5-VL 3B on Generic Android Phone (8GB RAM)?
Yes. Qwen2.5-VL 3B runs on Generic Android Phone (8GB RAM) at Q4_K_M (~4.4 GB of ~4.5 GB usable).
Fits at Q4_K_M (~4.4 GB of ~4.5 GB usable) but with little headroom, close other apps.
- Q4_K_M needed
- ~4.4 GB
- Usable on device
- ~4.5 GB
- Device memory
- 8 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
- 3.75B
- Q4_K_M size
- 3.05 GB
- Q8_0 size
- 5.1 GB
- Context
- 32k
- Memory
- 8 GB ram
- Usable for weights
- ~4.5 GB
- Best runtime
- llama.cpp (PocketPal or SmolChat)
You could also run
Run Qwen2.5-VL 3B on other hardware
FAQ
Can Generic Android Phone (8GB RAM) run Qwen2.5-VL 3B?
Yes. Qwen2.5-VL 3B runs on Generic Android Phone (8GB RAM) at Q4_K_M (~4.4 GB of ~4.5 GB usable).
How much memory does Qwen2.5-VL 3B need?
It is a tight fit on Generic Android Phone (8GB RAM). At Q4_K_M the weights are ~3.05 GB; with KV cache and runtime overhead, budget ~4.4 GB at a 4k context.
What is the best tool to run Qwen2.5-VL 3B 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.