text model · SmolLM2 · Android
Can I run SmolLM2 360M on Generic Android Phone (8GB RAM)?
Yes. SmolLM2 360M runs on Generic Android Phone (8GB RAM) at Q4_K_M (~1.2 GB of ~4.5 GB usable).
Runs at Q4_K_M using ~1.2 GB of ~4.5 GB usable. You have room for FP16 for higher quality.
- Q4_K_M needed
- ~1.2 GB
- Usable on device
- ~4.5 GB
- Device memory
- 8 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
- 0.362B
- Q4_K_M size
- 0.271 GB
- Q8_0 size
- 0.386 GB
- Context
- 2k
- Ollama tag
- smollm2:360m
- Memory
- 8 GB ram
- Usable for weights
- ~4.5 GB
- Best runtime
- llama.cpp (PocketPal or SmolChat)
You could also run
Run SmolLM2 360M on other hardware
FAQ
Can Generic Android Phone (8GB RAM) run SmolLM2 360M?
Yes. SmolLM2 360M runs on Generic Android Phone (8GB RAM) at Q4_K_M (~1.2 GB of ~4.5 GB usable).
How much memory does SmolLM2 360M need?
Generic Android Phone (8GB RAM) has room to spare. At Q4_K_M the weights are ~0.271 GB; with KV cache and runtime overhead, budget ~1.2 GB at a 4k context.
What is the best tool to run SmolLM2 360M 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.