Get started with Vanta
Choose a server, on-device model or cloud provider, save a model preset, and send your first message in Vanta on iPhone or iPad.
You need one working model to start. It can run on your iPhone or iPad, on a computer you control, or at a cloud provider. Vanta supplies the chat interface; you choose the model and where it runs.
1. Choose a starting point
| You already have… | Start with… |
|---|---|
| LM Studio on a computer | The LM Studio guide |
| Ollama on a computer or server | The Ollama guide |
| A vLLM server | The vLLM guide |
| A cloud API key | Cloud providers |
| No server or API account | On-device models |
Apple Intelligence can be a quick starting point on an eligible device with the system model available. A supported downloaded model is another option; its size must fit your device’s memory.
2. Add the source
For a server or custom cloud endpoint, open Settings → Providers → Add provider. Enter the API base address and a key if the server requires one. A local address such as 192.168.1.10:1234 belongs to your computer; localhost refers to the phone itself.
For downloaded models, open Local AI in Settings and choose a supported model or import a GGUF file. Finish its download before starting a local chat.
3. Save and select a model
A preset remembers the model and its settings. Create a preset for your connected provider or downloaded model, then select it in Settings → Models. The model picker in the chat also lets you switch between saved presets.
Use the exact model identifier supplied by a remote server. A friendly preset name is just for you; it does not change the model the server runs.
4. Send a simple first message
Start a new chat and ask: “Say hello in one sentence.” Check that the response finishes. Keep this first check free of files and tools so a connection problem is easy to identify.
After basic chat works, add a PDF, configure MCP tools, or adjust your preset. Choose a vision-capable model before attaching an image.
Before using sensitive information
Read privacy and data flow. A remote model receives the context assembled for the request. A local model keeps inference on-device, but separately configured tools, embeddings and cloud speech can still make network requests.
If the first message fails, use troubleshooting or contact support.
Your next chat starts here.
One purchase. Your choice of models.