text model · Qwen3 · iOS
Can I run Qwen3 0.6B on iPad Pro M4 (16GB, 1TB/2TB config)?
Yes. Qwen3 0.6B runs on iPad Pro M4 (16GB, 1TB/2TB config) at Q4_K_M (~1.5 GB of ~12 GB usable).
Runs at Q4_K_M using ~1.5 GB of ~12 GB usable. You have room for FP16 for higher quality.
- Q4_K_M needed
- ~1.5 GB
- Usable on device
- ~12 GB
- Device memory
- 16 GB
- Best quant
- Q4_K_M
How to run it
On iOS use Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.). Phones realistically run 1B-4B class models. Anything larger thermally throttles or OOMs.
- Parameters
- 0.6B
- Q4_K_M size
- 0.48 GB
- Q8_0 size
- 0.8 GB
- Context
- 32k
- Ollama tag
- qwen3:0.6b
- Memory
- 16 GB unified
- Usable for weights
- ~12 GB
- Best runtime
- MLX (via Python or Swift; mlx-lm package)
You could also run
Run Qwen3 0.6B on other hardware
FAQ
Can iPad Pro M4 (16GB, 1TB/2TB config) run Qwen3 0.6B?
Yes. Qwen3 0.6B runs on iPad Pro M4 (16GB, 1TB/2TB config) at Q4_K_M (~1.5 GB of ~12 GB usable).
How much memory does Qwen3 0.6B need?
iPad Pro M4 (16GB, 1TB/2TB config) has room to spare. At Q4_K_M the weights are ~0.48 GB; with KV cache and runtime overhead, budget ~1.5 GB at a 4k context.
What is the best tool to run Qwen3 0.6B 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.
Sources
Memory figures are estimates. See methodology.