text model · DeepSeek-R1-Distill · iOS
Can I run DeepSeek-R1-Distill-Qwen 14B on iPhone Air?
No. DeepSeek-R1-Distill-Qwen 14B needs ~10.7 GB even at Q4_K_M, but iPhone Air only has ~8 GB usable.
Needs ~10.7 GB even at Q4_K_M, but only ~8 GB is usable.
- Q4_K_M needed
- ~10.7 GB
- Usable on device
- ~8 GB
- Device memory
- 12 GB
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
- 14B
- Q4_K_M size
- 8.99 GB
- Q8_0 size
- 15.7 GB
- Context
- 128k
- Ollama tag
- deepseek-r1:14b
- Memory
- 12 GB unified
- Usable for weights
- ~8 GB
- Best runtime
- llama.cpp + Metal (via PocketPal or Off Grid app)
What you can run instead
Run DeepSeek-R1-Distill-Qwen 14B on other hardware
FAQ
Can iPhone Air run DeepSeek-R1-Distill-Qwen 14B?
No. DeepSeek-R1-Distill-Qwen 14B needs ~10.7 GB even at Q4_K_M, but iPhone Air only has ~8 GB usable.
How much memory does DeepSeek-R1-Distill-Qwen 14B need?
iPhone Air does not have enough memory. At Q4_K_M the weights are ~8.99 GB; with KV cache and runtime overhead, budget ~10.7 GB at a 4k context.
What is the best tool to run DeepSeek-R1-Distill-Qwen 14B 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.