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Run WhiteRabbitNeo 13B v1 on Mac

WhiteRabbitNeo 13B v1 runs 100% private on Mac inside Private LLM — no internet connection required, no data sent to any server.

13BMac

Download the quantized weights

These are the exact OmniQuant weights Private LLM runs for WhiteRabbitNeo 13B v1, published on our Hugging Face org. They're standard weights you can load in any app that supports the format, not just Private LLM.

Specifications

Parameters
13B
Context window
16K tokens
License
Llama 2
Quantization
OmniQuant 4-bit
Family
CodeLlama 13B

What WhiteRabbitNeo 13B v1 is good at

WhiteRabbitNeo is a 13 billion parameter AI model designed for offensive and defensive cybersecurity tasks. It can help with activities like network scanning, password cracking, and exploitation, but it is intended only for legal and ethical use. The model is released as a public preview to test its capabilities and understand its societal impact.

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)

Browse every model that fits iPhone or Mac.

How to run WhiteRabbitNeo 13B v1 in Private LLM

  1. Download Private LLM from the App Store.
  2. Open the in-app model library and choose WhiteRabbitNeo 13B v1.
  3. Download the model once, then chat fully offline.
Download Private LLM on the App StoreJoin our Discord

Variants & related models

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CodeNinja 1.0 OpenChat 7B

7.2B
coding
8K contextiPhone & iPad · Mac
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Llama 3 WhiteRabbitNeo 8B v2.0

8B
coding
8K contextiPhone & iPad · Mac
Qwen logo

Qwen 2.5 Coder 0.5B Unquantized

0.5B
coding
33K contextiPhone & iPad · Mac

Frequently asked questions

  • WhiteRabbitNeo 13B v1 is too large for current iPhones. It runs on Mac with enough unified memory inside Private LLM, fully offline.

  • Yes. WhiteRabbitNeo 13B v1 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), fully on-device in Private LLM.

  • Yes. Once downloaded in Private LLM, WhiteRabbitNeo 13B v1 runs 100% on-device — no internet connection, and nothing is sent to any server.

  • 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 WhiteRabbitNeo 13B v1 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 WhiteRabbitNeo 13B v1 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.

Specifications and summary come from WhiteRabbitNeo 13B v1's Hugging Face model card, 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.