[Models](/models) / [Mistral 7B](/models?family=Mistral%207B#models-gallery) / Zephyr 7B Beta

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

# Run Zephyr 7B Beta on Mac

Zephyr 7B Beta runs 100% private on Mac inside Private LLM — no internet connection required, no data sent to any server.

7.2BMac

## Download the quantized weights

These are the exact OmniQuant weights Private LLM runs for Zephyr 7B Beta, 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/zephyr-7b-beta-w4a16g128asym)

## Specifications

Parameters

7.2B

Context window

33K tokens

License

MIT

Quantization

OmniQuant 4-bit

Family

Mistral 7B

## What Zephyr 7B Beta is good at

general

Zephyr 7B Beta is a fine-tuned version of the Mistral 7B language model designed to act as a helpful assistant. It was trained using publicly available synthetic data and a method called Direct Preference Optimization. The model is good at general chat tasks and achieved high scores on benchmarks like MT Bench, but it may struggle with complex coding or math and can produce problematic content if prompted.

## 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)MacBook Pro (M4 Max, 48GB)MacBook Pro (M4 Max, 36GB)Mac (Apple Silicon, 32GB)MacBook Air (M4, 24GB)MacBook Air (M-series, 16GB)Mac (Apple Silicon, 8GB)

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

## How to run Zephyr 7B Beta in Private LLM

1.  Download Private LLM from the App Store.
2.  Open the in-app model library and choose Zephyr 7B Beta.
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

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

### Airoboros M 7B

7.2B

general

33K contextMac

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

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

### BioMistral 7B

7B

biomedical

33K contextMac

[View details →](/models/biomistral-7b)

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

### Cerbero 7B

7B

multilingual

33K contextMac

[View details →](/models/cerbero-7b)

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

### CodeNinja 1.0 OpenChat 7B

7.2B

coding

8K contextiPhone & iPad · Mac

[View details →](/models/codeninja-1.0-openchat-7b)

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

### DictaLM 2.0 Instruct

7.3B

multilingual

33K contextiPhone & iPad · Mac

[View details →](/models/dictalm2.0-instruct)

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

### Dolphin 2.1 Mistral

7.2B

uncensored

33K contextMac

[View details →](/models/dolphin-2.1-mistral-7b)

## Frequently asked questions

-   Can I run Zephyr 7B Beta on iPhone?
    
    Zephyr 7B Beta is too large for current iPhones. It runs on Mac with enough unified memory inside Private LLM, fully offline.
    
-   Can I run Zephyr 7B Beta on Mac?
    
    Yes. Zephyr 7B Beta 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), MacBook Pro (M4 Max, 48GB), MacBook Pro (M4 Max, 36GB), Mac (Apple Silicon, 32GB), MacBook Air (M4, 24GB), MacBook Air (M-series, 16GB), Mac (Apple Silicon, 8GB), fully on-device in Private LLM.
    
-   Does Zephyr 7B Beta work offline?
    
    Yes. Once downloaded in Private LLM, Zephyr 7B Beta runs 100% on-device — no internet connection, and nothing is sent to any server.
    
-   Is Zephyr 7B Beta 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 Zephyr 7B Beta 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 Zephyr 7B Beta 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 Zephyr 7B Beta's [Hugging Face model card](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta), released under the MIT license. Private LLM ships its own quantized models, built with OmniQuant quantization tuned per model, and isn't affiliated with the model's authors.