text model · Qwen2.5-Coder · Android
Can I run Qwen2.5 Coder 14B on Generic Android Phone (8GB RAM)?
No. Qwen2.5 Coder 14B needs ~10.1 GB even at Q4_K_M, but Generic Android Phone (8GB RAM) only has ~4.5 GB usable.
Needs ~10.1 GB even at Q4_K_M, but only ~4.5 GB is usable.
- Q4_K_M needed
- ~10.1 GB
- Usable on device
- ~4.5 GB
- Device memory
- 8 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
- 14B
- Q4_K_M size
- 8.37 GB
- Q8_0 size
- 14.62 GB
- Context
- 32k
- Ollama tag
- qwen2.5-coder:14b
- Memory
- 8 GB ram
- Usable for weights
- ~4.5 GB
- Best runtime
- llama.cpp (PocketPal or SmolChat)
What you can run instead
Run Qwen2.5 Coder 14B on other hardware
FAQ
Can Generic Android Phone (8GB RAM) run Qwen2.5 Coder 14B?
No. Qwen2.5 Coder 14B needs ~10.1 GB even at Q4_K_M, but Generic Android Phone (8GB RAM) only has ~4.5 GB usable.
How much memory does Qwen2.5 Coder 14B need?
Generic Android Phone (8GB RAM) does not have enough memory. 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.