Run Gemma 2B IT on iPhone, iPad & Mac
Gemma 2B IT runs 100% private on iPhone, iPad & Mac inside Private LLM — no internet connection required, no data sent to any server.
Download the quantized weights
These are the exact OmniQuant weights Private LLM runs for Gemma 2B IT, 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
- 2.5B
- License
- Gemma
- Quantization
- OmniQuant 4-bit
- Family
- Gemma
What Gemma 2B IT is good at
Gemma 2B IT is part of the Gemma family, tuned for general use on Apple devices.
Which of your devices can run it
iPhone
iPad
Mac
How to run Gemma 2B IT in Private LLM
- Download Private LLM from the App Store.
- Open the in-app model library and choose Gemma 2B IT.
- Download the model once, then chat fully offline.
Variants & related models
Frequently asked questions
Yes. Gemma 2B IT runs on iPhone models with enough memory, such as iPhone 17 Pro Max, iPhone 17 Pro, iPhone Air, iPhone 17, iPhone 16 Pro / 16 Pro Max, iPhone 16 / 16 Plus, iPhone 16e, iPhone 15 Pro / 15 Pro Max, fully on-device in Private LLM — no internet connection required.
Yes. Gemma 2B IT 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.
Yes. Once downloaded in Private LLM, Gemma 2B IT 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 Gemma 2B IT 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 Gemma 2B IT 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 Gemma 2B IT's Hugging Face model card, released under the Gemma license. Private LLM ships its own quantized models, built with OmniQuant quantization tuned per model, and isn't affiliated with the model's authors.