text model · DeepSeek-V3 · Android
Can I run DeepSeek V3 on Generic Android Phone (12GB RAM)?
No. DeepSeek V3 needs ~383.7 GB even at Q4_K_M, but Generic Android Phone (12GB RAM) only has ~8.5 GB usable.
Needs ~383.7 GB even at Q4_K_M, but only ~8.5 GB is usable.
- Q4_K_M needed
- ~383.7 GB
- Usable on device
- ~8.5 GB
- Device memory
- 12 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
- 671B (MoE, 37B active)
- Q4_K_M size
- 376.66 GB
- Context
- 128k
- Ollama tag
- deepseek-v3:671b
- Memory
- 12 GB ram
- Usable for weights
- ~8.5 GB
- Best runtime
- llama.cpp (PocketPal) or MLC-LLM
What you can run instead
FAQ
Can Generic Android Phone (12GB RAM) run DeepSeek V3?
No. DeepSeek V3 needs ~383.7 GB even at Q4_K_M, but Generic Android Phone (12GB RAM) only has ~8.5 GB usable.
How much memory does DeepSeek V3 need?
Generic Android Phone (12GB RAM) does not have enough memory. At Q4_K_M the weights are ~376.66 GB; with KV cache and runtime overhead, budget ~383.7 GB at a 4k context. It is a Mixture-of-Experts model (671B total / 37B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run DeepSeek V3 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.