Can you use AI on a Mac without a subscription?
Yes. Apple Silicon Macs can run local language models through MLX, Ollama, LM Studio, or apps that bundle local model support. Vehla uses this approach for Local AI: model inference can stay on your Mac, while BYOK cloud providers remain available when you want stronger hosted models and are comfortable sending that prompt to the provider you selected.
What does local AI actually mean?
Local AI means the model runs on your device or on a local server you control. In Vehla, the most private path is a bundled Gemma 4 model running through MLX on Apple Silicon. Ollama and LM Studio are local server routes. BYOK cloud providers are different: your Mac sends the prompt directly to OpenAI, Anthropic, Gemini, DeepSeek, or OpenRouter using your own key.
Which local AI route should Mac users choose?
| Route | Best for | Trade-off |
|---|---|---|
| Vehla + MLX | Keyboard-driven actions, rewrite, summarize, Recall, and private Mac workflows | Apple Silicon only |
| Ollama | Developers who want many open models and a local API | Requires model/server management |
| LM Studio | Testing local models with a friendly UI | Separate app and server setup |
| BYOK cloud | Highest model quality and vision/web tasks | Prompt leaves your Mac for the selected provider |
How does Vehla use local AI?
Vehla lets you switch between local and cloud routes from the palette. Sensitive drafts, notes, contracts, and internal code can use local Gemma 4 or imported MLX-compatible models. Tasks that need frontier hosted models can use your own provider keys. The practical benefit is not only privacy; it is speed of access. The model choice lives beside your Mac actions instead of in a separate chatbot tab.
What are the limitations of local AI?
Local models are not magic. Smaller quantized models can be slower, less knowledgeable, or less capable than hosted frontier models. They also require disk space and memory. Vehla exposes model size and lets you relocate downloads because storage matters. The honest workflow is hybrid: local for private routine work, BYOK cloud when quality or specialized capabilities matter.
What should you try first?
- Start with a small local model and test rewrite, summarize, and code explanation tasks.
- Use the same prompt against a BYOK cloud model and compare output quality.
- Keep a local route for private work even if you use cloud models for harder tasks.
- Document which prompts are safe to send to each route.
Related reading: Why we made local-first the default and Notes on Gemma 4 on Apple Silicon.