text model · LFM · iOS

Can I run LFM2.5 8B-A1B on iPad Pro M4 (16GB, 1TB/2TB config)?

Compatibility verdict VRAM threshold engine

Yes, it runs usable speed

Yes. LFM2.5 8B-A1B runs on iPad Pro M4 (16GB, 1TB/2TB config) at Q4_K_M (~6.7 GB of ~12 GB usable).

Needs ~6.7 GB Device usable ~12 GB

Runs at Q4_K_M using ~6.7 GB of ~12 GB usable. You have room for Q8_0 for higher quality.

That figure is at a 4k context and moves about ±15% as context length changes. iPad Pro M4 (16GB, 1TB/2TB config) leaves ~5.3 GB of headroom, room to step up to Q8_0 for higher quality.

Q4_K_M needed: ~6.7 GB
Usable on device: ~12 GB
Device memory: 16 GB
Best quant: Q4_K_M

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Which quant fits

Quant ladder vs ~12 GB usable

Q2_K

~5 GB

Q3_K_M

~5.6 GB

Q4_K_M

~6.7 GB

Q5_K_M

~7.4 GB

Q6_K

~8.3 GB

Q8_0

~10.5 GB

FP16

~18.5 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 LFM

Parameters: 8.3B (MoE, 1.5B active)
Q4_K_M size: 5.2 GB
Q8_0 size: 9 GB
Context: 128k
Ollama tag: lfm2.5:8b-a1b

Full LFM2.5 8B-A1B 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) →

You could also run

Run LFM2.5 8B-A1B on other hardware

Nvidia GeForce RTX 3060 (12GB)Nvidia GeForce RTX 4070 (12GB)Samsung Galaxy S24 Ultra Generic Android Phone (12GB RAM)iPhone 17 Pro iPhone Air

FAQ

Can iPad Pro M4 (16GB, 1TB/2TB config) run LFM2.5 8B-A1B?

Yes. LFM2.5 8B-A1B runs on iPad Pro M4 (16GB, 1TB/2TB config) at Q4_K_M (~6.7 GB of ~12 GB usable).

How much memory does LFM2.5 8B-A1B need?

iPad Pro M4 (16GB, 1TB/2TB config) has room to spare. At Q4_K_M the weights are ~5.2 GB; with KV cache and runtime overhead, budget ~6.7 GB at a 4k context. It is a Mixture-of-Experts model (8.3B total / 1.5B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run LFM2.5 8B-A1B 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

[![LFM2.5 8B-A1B on iPad Pro M4 (16GB, 1TB/2TB config)](https://localmodel.run/badge/lfm2.5-8b-a1b/ipad-pro-m4-16gb.svg)](https://localmodel.run/can-i-run/lfm2.5-8b-a1b/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.