text model · Hunyuan · iOS

Can I run Hunyuan-A13B-Instruct on iPad Pro M4 (16GB, 1TB/2TB config)?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Hunyuan-A13B-Instruct needs ~48.3 GB even at Q4_K_M, but iPad Pro M4 (16GB, 1TB/2TB config) only has ~12 GB usable.

Needs ~48.3 GB Device usable ~12 GB

Needs ~48.3 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 36.3 GB: Hunyuan-A13B-Instruct needs roughly 48.3 GB at Q4_K_M and iPad Pro M4 (16GB, 1TB/2TB config) leaves only about 12 GB usable for a model. The lightest tracked hardware that runs Hunyuan-A13B-Instruct is the Apple M4 Max (128GB) at 128 GB. See Hunyuan-A13B-Instruct on Apple M4 Max (128GB).

Q4_K_M needed: ~48.3 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

~36.4 GB

Q3_K_M

~42 GB

Q4_K_M

~48.3 GB

Q5_K_M

~59.9 GB

Q6_K

~68.5 GB

Q8_0

~82.5 GB

FP16

~163.9 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 Hunyuan

Parameters: 80B (MoE, 13B active)
Q4_K_M size: 45.43 GB
Q8_0 size: 79.58 GB
Context: 256k

Full Hunyuan-A13B-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

Run Hunyuan-A13B-Instruct on other hardware

Apple M4 Max (128GB)AMD Ryzen AI Halo (128GB)Apple M5 Max (128GB)Apple M3 Ultra (256GB)

FAQ

Can iPad Pro M4 (16GB, 1TB/2TB config) run Hunyuan-A13B-Instruct?

No. Hunyuan-A13B-Instruct needs ~48.3 GB even at Q4_K_M, but iPad Pro M4 (16GB, 1TB/2TB config) only has ~12 GB usable.

How much memory does Hunyuan-A13B-Instruct need?

iPad Pro M4 (16GB, 1TB/2TB config) does not have enough memory. At Q4_K_M the weights are ~45.43 GB; with KV cache and runtime overhead, budget ~48.3 GB at a 4k context. It is a Mixture-of-Experts model (80B total / 13B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run Hunyuan-A13B-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

[![Hunyuan-A13B-Instruct on iPad Pro M4 (16GB, 1TB/2TB config)](https://localmodel.run/badge/hunyuan-a13b/ipad-pro-m4-16gb.svg)](https://localmodel.run/can-i-run/hunyuan-a13b/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.