> ## AI Agent Context
> Get the complete documentation index at: https://aistudio.google.com/llms.txt
> Use this file to discover all available pages.
> For the full documentation in a single file, fetch: https://aistudio.google.com/llms-full.txt

# Gemini Developer API vs. Gemini platform

When developing generative AI solutions with Gemini, Google offers two API
products: the [Gemini Developer API](/docs) and the
[Gemini platform API](https://cloud.google.com/gemini-enterprise-agent-platform/overview).

The Gemini Developer API provides the fastest path to build, productionize, and
scale Gemini powered applications. Most developers should use the Gemini
Developer API unless there is a need for specific enterprise controls.

Gemini platform offers a comprehensive ecosystem of enterprise
ready features and services for building and deploying generative AI
applications backed by Google Cloud.

We've recently simplified migrating between these services. Both the Gemini
Developer API and the Gemini platform API are now accessible
through the unified [Google GenAI SDK](/docs/libraries) and the
[Interactions API](/docs/interactions-overview).

{% callout type="note" %}
   Note: If you're using an AI coding assistant, install
  the [Gemini API development skill](/docs/coding-agents) to give your agent
  access to the latest documentation and best practices. 

{% /callout %}

## Code comparison: Interactions API (recommended)  {% id="interactions-api" %}

The [Interactions API](/docs/interactions-overview) is the recommended way to
build with Gemini models and agents. The following examples compare text
generation between the Gemini Developer API and Gemini platform.

### Python  {% id="interactions-python" %}

You can access both the Gemini Developer API and Gemini platform
services through the `google-genai` library (`>= 2.3.0`). See the
[libraries](/docs/libraries) page for instructions on how to install
`google-genai`.

{% tabs %}
  {% tab label="Gemini Developer API" %}
  ```py
  from google import genai
  
  client = genai.Client()
  
  interaction = client.interactions.create(
      model="gemini-3.8-flash",
      input="Explain how AI works in a few words",
  )
  print(interaction.output_text)
  ```

  {% /tab %}

  {% tab label="Gemini platform API" %}
  ```py
  from google import genai
  
  client = genai.Client(
      enterprise=True, project="your-project-id", location="global"
  )
  
  interaction = client.interactions.create(
      model="gemini-3.8-flash",
      input="Explain how AI works in a few words",
  )
  print(interaction.output_text)
  ```

  {% /tab %}

{% /tabs %}

### JavaScript and TypeScript  {% id="interactions-javascript-and-typescript" %}

You can access both Gemini Developer API and Gemini platform
services through the `@google/genai` library (`>= 2.3.0`). See the
[libraries](/docs/libraries) page for instructions on how to install
`@google/genai`.

{% tabs %}
  {% tab label="Gemini Developer API" %}
  ```javascript
  import { GoogleGenAI } from "@google/genai";
  
  const ai = new GoogleGenAI({});
  
  const interaction = await ai.interactions.create({
    model: "gemini-3.8-flash",
    input: "Explain how AI works in a few words",
  });
  console.log(interaction.output_text);
  ```

  {% /tab %}

  {% tab label="Gemini platform API" %}
  ```javascript
  import { GoogleGenAI } from "@google/genai";
  
  const ai = new GoogleGenAI({
    enterprise: true,
    project: "your_project",
    location: "global",
  });
  
  const interaction = await ai.interactions.create({
    model: "gemini-3.8-flash",
    input: "Explain how AI works in a few words",
  });
  console.log(interaction.output_text);
  ```

  {% /tab %}

{% /tabs %}

## Code comparison: generateContent API  {% id="generate-content-api" %}

While the Interactions API is recommended for new projects, the
`generateContent` API remains supported.

### Python  {% id="python" %}

You can access both the Gemini Developer API and Gemini platform
services through the `google-genai` library. See the
[libraries](/docs/libraries) page for instructions on how to install
`google-genai`.

{% tabs %}
  

  {% tab label="Gemini Developer API" %}
  ```py
  from google import genai
  
  client = genai.Client()
  
  response = client.models.generate_content(
      model="gemini-3.8-flash", contents="Explain how AI works in a few words"
  )
  print(response.text)
  ```

  {% /tab %}

  

  {% tab label="Gemini platform API" %}
  ```py
  from google import genai
  
  client = genai.Client(
      vertexai=True, project='your-project-id', location='us-central1'
  )
  
  response = client.models.generate_content(
      model="gemini-3.8-flash", contents="Explain how AI works in a few words"
  )
  print(response.text)
  ```

  {% /tab %}

  

{% /tabs %}

### JavaScript and TypeScript  {% id="javascript-and-typescript" %}

You can access both Gemini Developer API and Gemini platform
services through `@google/genai` library. See [libraries](/docs/libraries) page
for instructions on how to install `@google/genai`.

{% tabs %}
  

  {% tab label="Gemini Developer API" %}
  ```javascript
  import { GoogleGenAI } from "@google/genai";
  
  const ai = new GoogleGenAI({});
  
  async function main() {
    const response = await ai.models.generateContent({
      model: "gemini-3.8-flash",
      contents: "Explain how AI works in a few words",
    });
    console.log(response.text);
  }
  
  await main();
  ```

  {% /tab %}

  

  {% tab label="Gemini platform API" %}
  ```javascript
  import { GoogleGenAI } from '@google/genai';
  const ai = new GoogleGenAI({
     vertexai: true,
     project: 'your_project',
     location: 'your_location',
   });
  
   async function main() {
     const response = await ai.models.generateContent({
       model: "gemini-3.8-flash",
       contents: "Explain how AI works in a few words",
     });
     console.log(response.text);
   }
  
   await main();
  ```

  {% /tab %}

  

{% /tabs %}

### Go  {% id="go" %}

You can access both Gemini Developer API and Gemini platform
services through `google.golang.org/genai` library. See
[libraries](/docs/libraries) page for instructions on how to install
`google.golang.org/genai`.

{% tabs %}
  

  {% tab label="Gemini Developer API" %}
  ```go
  import (
    "context"
    "encoding/json"
    "fmt"
    "log"
    "google.golang.org/genai"
  )
  
  // Your Google API key
  const apiKey = "your-api-key"
  
  func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, nil)
    if err != nil {
        log.Fatal(err)
    }
  
    // Call the GenerateContent method.
    result, err := client.Models.GenerateContent(ctx, "gemini-3.8-flash", genai.Text("Tell me about New York?"), nil)
  
  }
  ```

  {% /tab %}

  

  {% tab label="Gemini platform API" %}
  ```go
  import (
    "context"
    "encoding/json"
    "fmt"
    "log"
    "google.golang.org/genai"
  )
  
  // Your Google Cloud project
  const project = "your-project"
  
  // A Google Cloud location like "us-central1"
  const location = "some-gcp-location"
  
  func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, &genai.ClientConfig
    {
             Project: project,
        Location: location,
        Backend: genai.BackendVertexAI,
    })
  
    // Call the GenerateContent method.
    result, err := client.Models.GenerateContent(ctx, "gemini-3.8-flash", genai.Text("Tell me about New York?"), nil)
  
  }
  ```

  {% /tab %}

  

{% /tabs %}

### Other use cases and platforms  {% id="other-use-cases-and-platforms" %}

Refer to use case specific guides on [Gemini Developer API Documentation](/docs)
and
[Gemini platform documentation](https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/docs/overview)
for other platforms and use cases.

## Migration considerations  {% id="migration-considerations" %}

When you migrate:

*     You'll need to use Google Cloud service accounts to authenticate. See the
  [Gemini platform documentation](https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/docs/overview)
  for more information.

*   You can use your existing Google Cloud project
  (the same one you used to generate your API key) or you can
  [create a new Google Cloud project](https://cloud.google.com/resource-manager/docs/creating-managing-projects).

*     Supported regions may differ between the Gemini Developer API and the
  Gemini platform API. During Preview, the
  [Interactions API on Gemini platform](https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/capabilities/interactions/)
  only supports the `global` endpoint (`location="global"`). See the list of
  [supported regions for generative AI on Google Cloud](https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/docs/learn/locations-genai).

*   Any models you created in Google AI Studio need to be retrained in Gemini platform.


If you no longer need to use your Gemini API key for the Gemini Developer API,
then follow security best practices and delete it.

To delete an API key:

1.   Open the
  [Google Cloud API Credentials](https://console.cloud.google.com/apis/credentials)
  page.

2.   Find the API key you want to delete and click the **Actions** icon.

3.   Select **Delete API key**.

4.   In the **Delete credential** modal, select **Delete**.

  Deleting an API key takes a few minutes to propagate. After
  propagation completes, any traffic using the deleted API key is rejected.


Important: If you have deleted a key that is still used in production and need
to recover it, see
[gcloud beta services api-keys undelete](https://cloud.google.com/sdk/gcloud/reference/beta/services/api-keys/undelete).

## Next steps  {% id="next-steps" %}

*   Explore the
  [Interactions API on Gemini platform](https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/capabilities/interactions/)
  developer guide.
* See the
  [Generative AI on Gemini platform overview](https://docs.cloud.google.com/gemini-enterprise-agent-platform/overview)
  to learn more about generative AI solutions on Gemini platform.