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Run Tiger Gemma 9B v3 on iPad & Mac

Uncensored roleplay and text generation finetune of Gemma 2 9B

Tiger Gemma 9B v3 runs 100% private on iPad & Mac inside Private LLM — no internet connection required, no data sent to any server.

9.2BiPadMacuncensored

Specifications

Parameters
9.2B
Context window
8K tokens
Quantization
OmniQuant 4-bit
Family
Gemma 2 9B

What Tiger Gemma 9B v3 is good at

Tiger Gemma 9B v3 is a decensored version of the Gemma 2 9B base model, tuned with SPPO and a custom dataset to strip out refusal and unwanted moralizing. It has 9.2 billion parameters and a context window of 8192 tokens, and is designed to handle uncensored roleplay and other sensitive text generation without typical safety filters.

Which of your devices can run it

iPad

iPad Pro (M5, 16GB)iPad Pro (M4, 16GB)iPad Pro (M2, 16GB)iPad Pro (M1, 16GB)

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 Tiger Gemma 9B v3 in Private LLM

  1. Download Private LLM from the App Store.
  2. Open the in-app model library and choose Tiger Gemma 9B v3.
  3. Download the model once, then chat fully offline.
Download Private LLM on the App StoreJoin our Discord

Variants & related models

Google Gemma logo

FuseChat Gemma 2 9B Instruct

9.2B

General-purpose assistant distilled from four larger models into Gemma 2 9B

8K contextiPhone & iPad · Mac
Google Gemma logo

Gemma 2 9B IT

9.2B

General-purpose model in the Gemma 2 9B family

iPhone & iPad · Mac
Google Gemma logo

Gemma 2 9B IT SPPO Iter3

9.2B

General assistant refined from Gemma 2 9B via three rounds of self-play training

8K contextiPhone & iPad · Mac
Google Gemma logo

Gemma 2 Ifable 9B

9B

Roleplay specialist ranked first for creative writing on Gemma 2 9B

8K contextiPhone & iPad · Mac
Google Gemma logo

Amoral Gemma 3 1B v2

1B

Uncensored Gemma 3 1B finetune for neutral factual responses

33K contextiPhone & iPad · Mac
DeepSeek logo

DeepSeek R1 Distill Llama 8B Abliterated

8B

Uncensored DeepSeek R1 Distill 8B via refusal abliteration

131K contextiPhone & iPad · Mac

Frequently asked questions

  • Tiger Gemma 9B v3 is too large for current iPhones. It runs on Mac with enough unified memory inside Private LLM, fully offline.

  • Yes. Tiger Gemma 9B v3 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, Tiger Gemma 9B v3 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 Tiger Gemma 9B v3 in Private LLM

Private LLM has run local AI on iPhone, iPad, and Mac since 2023, well before Apple Intelligence, LM Studio, Ollama, etc. existed. Inference happens on your device, so your Tiger Gemma 9B v3 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 Tiger Gemma 9B v3's Hugging Face model card. Private LLM ships its own quantized models, built with OmniQuant quantization tuned per model, and isn't affiliated with the model's authors.