text model · Sarvam · iOS
S Can I run Sarvam-30B on iPhone 17 Pro?
No. Sarvam-30B needs ~21.7 GB even at Q4_K_M, but iPhone 17 Pro only has ~8 GB usable.
Needs ~21.7 GB even at Q4_K_M, but only ~8 GB is usable.
- Q4_K_M needed
- ~21.7 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
- 30B (MoE, 2.4B active)
- Q4_K_M size
- 19.6 GB
- Context
- 64k
- 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 Sarvam-30B on other hardware
FAQ
Can iPhone 17 Pro run Sarvam-30B?
No. Sarvam-30B needs ~21.7 GB even at Q4_K_M, but iPhone 17 Pro only has ~8 GB usable.
How much memory does Sarvam-30B need?
iPhone 17 Pro does not have enough memory. At Q4_K_M the weights are ~19.6 GB; with KV cache and runtime overhead, budget ~21.7 GB at a 4k context. It is a Mixture-of-Experts model (30B total / 2.4B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run Sarvam-30B 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.