For the complete documentation index, see llms.txt. This page is also available as Markdown.

Hardware & Model Choices

BonzAI runs AI on your device. A more powerful computer can use larger models or finish media generation faster, but modest computers can still use smaller models and browser features.

The simple rule

  • 8 GB memory: start with small chat models and lighter browser workflows.

  • 16 GB memory: comfortable everyday chat, lighter image/audio work, and more model choice.

  • 24–32 GB memory: larger language models, stronger image workflows, and better multitasking.

  • High-end Apple Silicon or a dedicated NVIDIA GPU: best for large models, video, training, and high-resolution media.

Storage

Models can be much larger than the application.

  • Keep at least 10 GB free for a basic setup.

  • Keep 50 GB or more free if you want several language and media models.

  • Video, training checkpoints, and generation history can use additional space.

BonzAI shows download size before or during model installation. You can remove models you no longer use.

Choosing a language model

Your priority
Choose

Fast answers and low memory use

Small model

Everyday quality

Medium model

Difficult reasoning or long writing

Larger model that fits your hardware

Programming

A coder-focused model

Unrestricted local experimentation

A compatible abliterated model, where lawful

Quantization reduces model size. Lower-bit versions use less memory and usually run faster, but may lose some accuracy. BonzAI's recommendations are designed to make this tradeoff understandable.

Choosing media settings

  • Begin with SD or HD image resolution.

  • Use Turbo/Fast while exploring ideas.

  • Switch to higher quality once the prompt is working.

  • Generate shorter videos before committing to long clips.

  • Close unused large models before training or video generation.

Apple, NVIDIA, and CPU-only devices

BonzAI selects compatible acceleration when available:

  • Apple Silicon uses unified memory and Apple GPU acceleration.

  • NVIDIA systems use CUDA-capable paths where supported.

  • Other systems can use CPU or available fallback acceleration, but large media models may be slow.

The app's hardware information helps you choose; you do not need to configure acceleration manually.

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