text model · Kimi · iOS
Can I run Kimi K3 on iPhone 16?
No. Kimi K3 needs ~1522.2 GB even at Q4_K_M, but iPhone 16 only has ~4.5 GB usable.
Needs ~1522.2 GB even at Q4_K_M, but only ~4.5 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 1517.7 GB: Kimi K3 needs roughly 1522.2 GB at Q4_K_M and iPhone 16 leaves only about 4.5 GB usable for a model. No single tracked device has enough memory; Kimi K3 needs a multi-GPU or high-memory rig.
- Q4_K_M needed
- ~1522.2 GB
- Usable on device
- ~4.5 GB
- Device memory
- 8 GB
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
- 2800B (MoE, 104B active)
- Q4_K_M size
- 1508.67 GB
- Context
- 1000k
- Memory
- 8 GB unified
- Usable for weights
- ~4.5 GB
- Power draw
- ~11 W
- Best runtime
- llama.cpp + Metal (via PocketPal or Off Grid app)
What you can run instead
FAQ
Can iPhone 16 run Kimi K3?
No. Kimi K3 needs ~1522.2 GB even at Q4_K_M, but iPhone 16 only has ~4.5 GB usable.
How much memory does Kimi K3 need?
iPhone 16 does not have enough memory. At Q4_K_M the weights are ~1508.67 GB; with KV cache and runtime overhead, budget ~1522.2 GB at a 4k context. It is a Mixture-of-Experts model (2800B total / 104B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run Kimi K3 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/kimi-k3/iphone-16) 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.