[Models](/models) / [Llama 2 7B](/models?family=Llama%202%207B#models-gallery) / Xwin LM 7B v0.1

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

# Run Xwin LM 7B v0.1 on Mac

Xwin LM 7B v0.1 runs 100% private on Mac inside Private LLM — no internet connection required, no data sent to any server.

7BMac

## Download the quantized weights

These are the exact OmniQuant weights Private LLM runs for Xwin LM 7B v0.1, 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/Xwin-LM-7B-V0.1-w4a16g128asym)

## Specifications

Parameters

7B

Context window

4K tokens

License

Llama 2

Quantization

OmniQuant 4-bit

Family

Llama 2 7B

## What Xwin LM 7B v0.1 is good at

general

Xwin-LM is a family of large language models built on Llama 2, designed to follow instructions well. It is good at generating helpful and detailed responses in conversations. The 70B version was the first model to outperform GPT-4 on the AlpacaEval benchmark.

## 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 Xwin LM 7B v0.1 in Private LLM

1.  Download Private LLM from the App Store.
2.  Open the in-app model library and choose Xwin LM 7B v0.1.
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)

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

### Spicyboros 7b 2.2

7B

uncensored

4K contextiPhone & iPad · Mac

[View details →](/models/spicyboros-7b-2.2)

![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)

## Frequently asked questions

-   Can I run Xwin LM 7B v0.1 on iPhone?
    
    Xwin LM 7B v0.1 is too large for current iPhones. It runs on Mac with enough unified memory inside Private LLM, fully offline.
    
-   Can I run Xwin LM 7B v0.1 on Mac?
    
    Yes. Xwin LM 7B v0.1 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 Xwin LM 7B v0.1 work offline?
    
    Yes. Once downloaded in Private LLM, Xwin LM 7B v0.1 runs 100% on-device — no internet connection, and nothing is sent to any server.
    
-   Is Xwin LM 7B v0.1 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 Xwin LM 7B v0.1 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 Xwin LM 7B v0.1 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

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](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 Xwin LM 7B v0.1's [Hugging Face model card](https://huggingface.co/Xwin-LM/Xwin-LM-7B-V0.1), released under the Llama 2 license. Private LLM ships its own quantized models, built with OmniQuant quantization tuned per model, and isn't affiliated with the model's authors.