text model · DeepSeek-R1-Distill · Android
Can I run DeepSeek-R1-Distill-Qwen 32B on Samsung Galaxy S25 Ultra (16GB, 1TB config only)?
No. DeepSeek-R1-Distill-Qwen 32B needs ~22.1 GB even at Q4_K_M, but Samsung Galaxy S25 Ultra (16GB, 1TB config only) only has ~12 GB usable.
Needs ~22.1 GB even at Q4_K_M, but only ~12 GB is usable.
- Q4_K_M needed
- ~22.1 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
- 32B
- Q4_K_M size
- 19.85 GB
- Q8_0 size
- 34.82 GB
- Context
- 128k
- Ollama tag
- deepseek-r1:32b
- 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
Run DeepSeek-R1-Distill-Qwen 32B on other hardware
FAQ
Can Samsung Galaxy S25 Ultra (16GB, 1TB config only) run DeepSeek-R1-Distill-Qwen 32B?
No. DeepSeek-R1-Distill-Qwen 32B needs ~22.1 GB even at Q4_K_M, but Samsung Galaxy S25 Ultra (16GB, 1TB config only) only has ~12 GB usable.
How much memory does DeepSeek-R1-Distill-Qwen 32B need?
Samsung Galaxy S25 Ultra (16GB, 1TB config only) does not have enough memory. At Q4_K_M the weights are ~19.85 GB; with KV cache and runtime overhead, budget ~22.1 GB at a 4k context.
What is the best tool to run DeepSeek-R1-Distill-Qwen 32B 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.