text model · mistral · iOS
Can I run Mixtral 8x7B on iPhone 16 Pro?
No. Mixtral 8x7B needs ~28.9 GB even at Q4_K_M, but iPhone 16 Pro only has ~4.5 GB usable.
Needs ~28.9 GB even at Q4_K_M, but only ~4.5 GB is usable.
- Q4_K_M needed
- ~28.9 GB
- Usable on device
- ~4.5 GB
- Device memory
- 8 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
- 46.7B (MoE, 12.9B active)
- Q4_K_M size
- 26.49 GB
- Q8_0 size
- 46.22 GB
- Context
- 32k
- Ollama tag
- mixtral:8x7b
- Memory
- 8 GB unified
- Usable for weights
- ~4.5 GB
- Best runtime
- llama.cpp + Metal (via PocketPal or Off Grid app)
What you can run instead
Run Mixtral 8x7B on other hardware
FAQ
Can iPhone 16 Pro run Mixtral 8x7B?
No. Mixtral 8x7B needs ~28.9 GB even at Q4_K_M, but iPhone 16 Pro only has ~4.5 GB usable.
How much memory does Mixtral 8x7B need?
iPhone 16 Pro does not have enough memory. At Q4_K_M the weights are ~26.49 GB; with KV cache and runtime overhead, budget ~28.9 GB at a 4k context. It is a Mixture-of-Experts model (46.7B total / 12.9B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run Mixtral 8x7B 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.