text model · DeepSeek-V3 · Android
Can I run DeepSeek V3 on Samsung Galaxy S26 Ultra (16GB, 1TB config)?
No. DeepSeek V3 needs ~383.7 GB even at Q4_K_M, but Samsung Galaxy S26 Ultra (16GB, 1TB config) only has ~12 GB usable.
Needs ~383.7 GB even at Q4_K_M, but only ~12 GB is usable.
- Q4_K_M needed
- ~383.7 GB
- Usable on device
- ~12 GB
- Device memory
- 16 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
- 16 GB ram
- Usable for weights
- ~12 GB
- Best runtime
- llama.cpp (PocketPal) or MLC-LLM (Adreno GPU path)
What you can run instead
FAQ
Can Samsung Galaxy S26 Ultra (16GB, 1TB config) run DeepSeek V3?
No. DeepSeek V3 needs ~383.7 GB even at Q4_K_M, but Samsung Galaxy S26 Ultra (16GB, 1TB config) only has ~12 GB usable.
How much memory does DeepSeek V3 need?
Samsung Galaxy S26 Ultra (16GB, 1TB config) 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.