> ## Documentation Index
> Fetch the complete documentation index at: https://gomodel-docs-providers-restructure.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Google Vertex AI

> Configure Gemini on Google Vertex AI in GoModel, including ADC and service-account authentication, regions, and native vs OpenAI-compatible routing.

This page covers Gemini hosted on **Google Vertex AI**. For Gemini through
Google AI Studio API keys, see the [Google Gemini guide](/providers/gemini).

GoModel routes Vertex chat and Responses API requests through Vertex AI's
native Gemini publisher endpoint by default. You can switch to Vertex's
OpenAI-compatible endpoint when you need its compatibility behavior.

<Note>
  Vertex authentication is enterprise-oriented and may become paid or
  licensed in a future release.
</Note>

## Before you start

* A Google Cloud project with Vertex AI enabled.
* A Vertex region where the model you want is available (e.g. `us-central1`,
  `europe-west4`).
* Either Application Default Credentials (via `gcloud auth
  application-default login`, GKE Workload Identity, or a metadata server) or
  a service-account JSON key.

## Configure Vertex AI

Use the `VERTEX_*` prefix. Vertex providers use the dedicated `vertex`
provider type:

```bash theme={null}
export VERTEX_PROJECT="my-gcp-project"
export VERTEX_LOCATION="us-central1"
export VERTEX_AUTH_TYPE="gcp_adc"
export VERTEX_API_MODE="native"
```

This registers provider `vertex`, type `vertex`. Vertex requires both project
and location. `VERTEX_AUTH_TYPE` defaults to Application Default Credentials
(`gcp_adc`) when service-account fields are not set.

Or in `config.yaml`:

```yaml theme={null}
providers:
  vertex:
    type: vertex
    auth_type: gcp_adc
    vertex_project: my-gcp-project
    vertex_location: us-central1
    api_mode: native
```

## Service-account authentication

Use service-account JSON directly when ADC is not appropriate:

```bash theme={null}
export VERTEX_AUTH_TYPE="gcp_service_account"
export VERTEX_SERVICE_ACCOUNT_FILE="/secrets/service-account.json"
# or VERTEX_SERVICE_ACCOUNT_JSON / VERTEX_SERVICE_ACCOUNT_JSON_BASE64
```

## Multiple regions or accounts

For multiple Vertex regions or accounts, use suffixed env vars:

```bash theme={null}
export VERTEX_US_PROJECT="prod-ai"
export VERTEX_US_LOCATION="us-central1"
export VERTEX_US_AUTH_TYPE="gcp_adc"

export VERTEX_EU_PROJECT="prod-ai"
export VERTEX_EU_LOCATION="europe-west4"
export VERTEX_EU_AUTH_TYPE="gcp_service_account"
export VERTEX_EU_SERVICE_ACCOUNT_FILE="/secrets/vertex-eu.json"
```

These register providers `vertex_us` and `vertex_eu`.

## Native versus OpenAI-compatible mode

Vertex native mode is enabled by default:

```bash theme={null}
export VERTEX_API_MODE="native"
```

Set `VERTEX_API_MODE=openai_compatible` to route chat and Responses API
requests through Vertex's OpenAI-compatible endpoint instead.

The default Vertex bases are derived from project and location:

* OpenAI-compatible: `https://aiplatform.googleapis.com/v1/projects/{project}/locations/{location}/endpoints/openapi`
* native Gemini: `https://aiplatform.googleapis.com/v1/projects/{project}/locations/{location}/publishers/google`

Vertex embeddings use Vertex AI native prediction regardless of `VERTEX_API_MODE`.
Vertex does not expose Gemini Files or OpenAI-compatible batch operations.

## Image URL behavior

Like AI Studio Gemini, native mode supports inline image data only:

```json theme={null}
{
  "type": "image_url",
  "image_url": {
    "url": "data:image/jpeg;base64,..."
  }
}
```

Remote `https://...` image URLs are rejected in native mode. Set
`VERTEX_API_MODE=openai_compatible` to pass the OpenAI-compatible `image_url`
shape through to Vertex's OpenAI-compatible endpoint instead.

## Current support

Integrated:

* chat completions and streaming
* Responses API and streaming
* model listing via Vertex publisher models
* Vertex embeddings through native prediction
* usage metadata normalization for native responses
* tool calls and function-call results
* inline image data via `data:` URLs in native mode

Not integrated yet:

* fetching remote `image_url` values
* Vertex Files and batch prediction APIs

References:

* [Vertex AI OpenAI compatibility](https://cloud.google.com/vertex-ai/generative-ai/docs/start/openai)
* [Gemini API in Vertex AI](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference)
* [Application Default Credentials](https://cloud.google.com/docs/authentication/application-default-credentials)