text model · SmolLM3 · iOS
Can I run SmolLM3 3B on iPhone 17?
Yes. SmolLM3 3B runs on iPhone 17 at Q4_K_M (~3 GB of ~4.5 GB usable).
Runs at Q4_K_M using ~3 GB of ~4.5 GB usable. You have room for Q8_0 for higher quality.
That figure is at a 4k context and moves about ±15% as context length changes. iPhone 17 leaves ~1.5 GB of headroom, room to step up to Q8_0 for higher quality.
- Q4_K_M needed
- ~3 GB
- Usable on device
- ~4.5 GB
- Device memory
- 8 GB
- Best quant
- Q4_K_M
Which quant fits
How to run it
On iOS use Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.).
- Parameters
- 3B
- Q4_K_M size
- 1.78 GB
- Q8_0 size
- 3.05 GB
- Context
- 128k
- Memory
- 8 GB unified
- Usable for weights
- ~4.5 GB
- Best runtime
- llama.cpp + Metal (via PocketPal or Off Grid app)
You could also run
Run SmolLM3 3B on other hardware
FAQ
Can iPhone 17 run SmolLM3 3B?
Yes. SmolLM3 3B runs on iPhone 17 at Q4_K_M (~3 GB of ~4.5 GB usable).
How much memory does SmolLM3 3B need?
iPhone 17 has room to spare. At Q4_K_M the weights are ~1.78 GB; with KV cache and runtime overhead, budget ~3 GB at a 4k context.
What is the best tool to run SmolLM3 3B on iOS?
On iPhone and iPad, Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.) is the standard choice. Phones realistically run 1B-4B class models. Anything larger thermally throttles or OOMs.
Embed this
A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/smollm3-3b/iphone-17) Sources
Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.