text model · Kimi · iOS

Can I run Kimi K2 Instruct on iPad Pro M4 (16GB, 1TB/2TB config)?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Kimi K2 Instruct needs ~586.6 GB even at Q4_K_M, but iPad Pro M4 (16GB, 1TB/2TB config) only has ~12 GB usable.

Needs ~586.6 GB Device usable ~12 GB

Needs ~586.6 GB even at Q4_K_M, but only ~12 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 574.6 GB: Kimi K2 Instruct needs roughly 586.6 GB at Q4_K_M and iPad Pro M4 (16GB, 1TB/2TB config) leaves only about 12 GB usable for a model. No single tracked device has enough memory; Kimi K2 Instruct needs a multi-GPU or high-memory rig.

Q4_K_M needed: ~586.6 GB
Usable on device: ~12 GB
Device memory: 16 GB

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Which quant fits

Quant ladder vs ~12 GB usable

Q2_K

~427.2 GB

Q3_K_M

~497.2 GB

Q4_K_M

~586.6 GB

Q5_K_M

~720.9 GB

Q6_K

~828.4 GB

Q8_0

~1024.5 GB

FP16

~2008.4 GB

The line marks iPad Pro M4 (16GB, 1TB/2TB config)'s ~12 GB budget; rungs past it are too large.

How to run it

On iOS use Apple Foundation Models (Built into iOS 26, ~3B on-device model, zero download, fully private.).

Model Kimi

Parameters: 1000B (MoE, 32B active)
Q4_K_M size: 578.15 GB
Q8_0 size: 1016.12 GB
Context: 128k
Ollama tag: kimi-k2

Full Kimi K2 Instruct requirements →

Device iOS

Memory: 16 GB unified
Usable for weights: ~12 GB
Power draw: ~14 W
Best runtime: MLX (via Python or Swift; mlx-lm package)

Best models for iPad Pro M4 (16GB, 1TB/2TB config) →

What you can run instead

FAQ

Can iPad Pro M4 (16GB, 1TB/2TB config) run Kimi K2 Instruct?

No. Kimi K2 Instruct needs ~586.6 GB even at Q4_K_M, but iPad Pro M4 (16GB, 1TB/2TB config) only has ~12 GB usable.

How much memory does Kimi K2 Instruct need?

iPad Pro M4 (16GB, 1TB/2TB config) does not have enough memory. At Q4_K_M the weights are ~578.15 GB; with KV cache and runtime overhead, budget ~586.6 GB at a 4k context. It is a Mixture-of-Experts model (1000B total / 32B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run Kimi K2 Instruct 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.

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Markdown

[![Kimi K2 Instruct on iPad Pro M4 (16GB, 1TB/2TB config)](https://localmodel.run/badge/kimi-k2/ipad-pro-m4-16gb.svg)](https://localmodel.run/can-i-run/kimi-k2/ipad-pro-m4-16gb)

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.