[Models](/models) / [Llama 3.1 70B](/models?family=Llama%203.1%2070B#models-gallery) / Meta Llama 3.1 70B Instruct

![Meta logo](/model-logos/meta.svg)

# Run Meta Llama 3.1 70B Instruct on Mac

Meta Llama 3.1 70B Instruct runs 100% private on Mac inside Private LLM — no internet connection required, no data sent to any server.

70.6BMac

## Download the quantized weights

These are the exact OmniQuant weights Private LLM runs for Meta Llama 3.1 70B Instruct, published on our Hugging Face org. They're standard weights you can load in any app that supports the format, not just Private LLM.

-   [Mac — 4-bit OmniQuant →](https://huggingface.co/numen-tech/Meta-Llama-3.1-70B-Instruct-w4a16g128asym)

## Specifications

Parameters

70.6B

License

Llama 3.1

Quantization

OmniQuant 4-bit

Family

Llama 3.1 70B

## What Meta Llama 3.1 70B Instruct is good at

general

Meta Llama 3.1 70B Instruct is part of the Llama 3.1 70B family, tuned for general use on Apple devices.

## Which of your devices can run it

### Mac

Mac (Apple Silicon, 192GB)MacBook Pro (M4 Max, 128GB)Mac Studio / Pro (Apple Silicon, 96GB)MacBook Pro (M4 Max, 64GB)

Browse every model that fits [iPhone](/models/best-for-iphone) or [Mac](/models/best-for-mac).

## How to run Meta Llama 3.1 70B Instruct in Private LLM

1.  Download Private LLM from the App Store.
2.  Open the in-app model library and choose Meta Llama 3.1 70B Instruct.
3.  Download the model once, then chat fully offline.

[![Download Private LLM on the App Store](/app-store/download-badge/en/download.svg)![Download Private LLM on the App Store](/app-store/download-badge/en/download-dark.svg)](/download)[Join our Discord](/discord)

## Variants & related models

![Meta logo](/model-logos/meta.svg)

### Airoboros l2 7b 3.0

6.7B

general

4K contextiPhone & iPad · Mac

[View details →](/models/airoboros-l2-7b-3.0)

![Mistral logo](/model-logos/mistral.svg)

### Airoboros M 7B

7.2B

general

33K contextMac

[View details →](/models/airoboros-m-7b-3.1.2)

![Meta logo](/model-logos/meta.svg)

### Cat Llama 3 70B Instruct

70.6B

general

8K contextMac

[View details →](/models/cat-llama-3-70b-instruct)

![Google Gemma logo](/model-logos/gemma.svg)

### FuseChat Gemma 2 9B Instruct

9.2B

general

8K contextiPhone & iPad · Mac

[View details →](/models/fusechat-gemma-2-9b-instruct)

![Meta logo](/model-logos/meta.svg)

### FuseChat Llama 3.1 8B Instruct

8B

general

131K contextiPhone & iPad · Mac

[View details →](/models/fusechat-llama-3.1-8b-instruct)

![Meta logo](/model-logos/meta.svg)

### FuseChat Llama 3.2 1B Instruct

1.2B

general

131K contextiPhone & iPad · Mac

[View details →](/models/fusechat-llama-3.2-1b-instruct)

## Frequently asked questions

-   Can I run Meta Llama 3.1 70B Instruct on iPhone?
    
    Meta Llama 3.1 70B Instruct is too large for current iPhones. It runs on Mac with enough unified memory inside Private LLM, fully offline.
    
-   Can I run Meta Llama 3.1 70B Instruct on Mac?
    
    Yes. Meta Llama 3.1 70B Instruct runs on Macs with enough unified memory, such as Mac (Apple Silicon, 192GB), MacBook Pro (M4 Max, 128GB), Mac Studio / Pro (Apple Silicon, 96GB), MacBook Pro (M4 Max, 64GB), fully on-device in Private LLM.
    
-   Does Meta Llama 3.1 70B Instruct work offline?
    
    Yes. Once downloaded in Private LLM, Meta Llama 3.1 70B Instruct runs 100% on-device — no internet connection, and nothing is sent to any server.
    
-   Is Meta Llama 3.1 70B Instruct free to use?
    
    Private LLM is a one-time purchase with no subscription and no per-message cost. The models themselves are open source — once downloaded, they run offline with nothing to pay per use.
    

## Why run Meta Llama 3.1 70B Instruct in Private LLM

Private LLM has run local AI on iPhone, iPad, and Mac since 2023, before Apple Intelligence existed. Inference happens on your device, so your Meta Llama 3.1 70B Instruct conversations never reach a server. The part most apps gloss over is quantization, and that is exactly where on-device quality is won or lost. Most llama.cpp and MLX wrappers ship the same off-the-shelf 4-bit RTN weights. Private LLM ships GPTQ and OmniQuant quantization, tuned per model, and our 3-bit OmniQuant models match or beat those 4-bit RTN builds on the same Apple Silicon. Run the same model both ways and you feel it in the first reply. [See how our quantization works](/en/faq#Why-can-t-Private-LLM-load-models-directly-from-Hugging-Face).

### More from Numen

[![Slop or Not app icon](/app-icons/slop-or-not.png)

#### Slop or Not

Catch AI-written text on iPhone and Mac. The check runs on-device, so nothing you paste gets uploaded.

](https://slopornot.ai)[![Clean Links app icon](/app-icons/clean-links.png)

#### Clean Links

Strip trackers and clutter from any link before you share it. The cleanup happens on your device.

](https://cleanlinks.app)

Specifications and summary come from Meta Llama 3.1 70B Instruct's [Hugging Face model card](https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct), released under the Llama 3.1 license. Private LLM ships its own quantized models, built with OmniQuant quantization tuned per model, and isn't affiliated with the model's authors.