text model · Qwen2.5-Coder · Android
Can I run Qwen2.5 Coder 14B on Google Pixel 10 Pro?
Yes. Qwen2.5 Coder 14B runs on Google Pixel 10 Pro at Q4_K_M (~10.1 GB of ~10.5 GB usable).
Fits at Q4_K_M (~10.1 GB of ~10.5 GB usable) but with little headroom, close other apps.
- Q4_K_M needed
- ~10.1 GB
- Usable on device
- ~10.5 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
- 14B
- Q4_K_M size
- 8.37 GB
- Q8_0 size
- 14.62 GB
- Context
- 32k
- Ollama tag
- qwen2.5-coder:14b
- Memory
- 16 GB ram
- Usable for weights
- ~10.5 GB
- Best runtime
- llama.cpp (PocketPal) or MLC-LLM (Adreno GPU path)
You could also run
Run Qwen2.5 Coder 14B on other hardware
FAQ
Can Google Pixel 10 Pro run Qwen2.5 Coder 14B?
Yes. Qwen2.5 Coder 14B runs on Google Pixel 10 Pro at Q4_K_M (~10.1 GB of ~10.5 GB usable).
How much memory does Qwen2.5 Coder 14B need?
It is a tight fit on Google Pixel 10 Pro. At Q4_K_M the weights are ~8.37 GB; with KV cache and runtime overhead, budget ~10.1 GB at a 4k context.
What is the best tool to run Qwen2.5 Coder 14B 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.