Fix Gemini API User Location Not Supported Error

If you are developing with the Gemini API and encounter a 403 Forbidden error with the message "User location is not supported for the API use" or REG_USER_LOCATION_NOT_SUPPORTED, your API requests are originating from an IP address outside of Google's supported regions.

This guide explains how to diagnose this geographic restriction and provides step-by-step solutions to configure your SDK, hosting environment, or proxy settings to resolve the error.

1. Verify Your IP Region and Gemini's Supported List Before changing code, confirm if your current physical location or your hosting provider's data center is officially supported by Google AI Studio.

1. Check the official Google Gemini API Available Regions list to verify if your country is included. 2. Determine the external IP address of the machine making the API call. Run this command in your terminal: `bash curl ifconfig.me ` 3. Perform a IP lookup on the returned address to verify which country and region your hosting network is routing traffic through. Many server providers route traffic through international gateways that differ from your local regional settings.

2. Lock Your Cloud Deployment Region If your local development environment works but your deployed application (e.g., on Vercel, AWS Lambda, Render, or Heroku) throws the unsupported location error, the application is likely running on an edge server in an unsupported data center region.

Configure your cloud deployment settings to force execution in a supported region: * For Vercel: Open your vercel.json file and specify a supported region (such as iad1 or sfo1 for the USA) for your Serverless Functions: `json { "regions": ["iad1"] } ` * For AWS Lambda: Redeploy your function to a supported region such as us-east-1 or eu-west-1 instead of using global edge routing (Lambda@Edge) which may route through restricted zones. * For Google Cloud Run / Functions: Deploy your container specifically to us-central1 or other supported regions rather than relying on automatic multi-region routing.

3. Route Requests Through a Server-Side Proxy If your application must run from an unsupported region, do not make API calls directly from the user's client browser. Client-side requests expose your API key and cause location errors if the end-user is in a restricted region. Instead, route the API calls through an intermediate server-side proxy located in a supported region.

1. Set up a minimal server-side endpoint (Node.js/Express, Python/FastAPI, or Next.js Route Handlers) on a server hosted in a supported region.
2. Have your client application call your custom backend endpoint.
3. Have your backend securely forward the payload to the Gemini API, receive the response, and return it to the client.

Example of a Next.js Serverless Route Handler (/api/gemini/route.js) hosted in a supported US region: `javascript import { GoogleGenAI } from '@google/generative-ai';

export async function POST(req) { const genAI = new GoogleGenAI(process.env.GEMINI_API_KEY); const model = genAI.getGenerativeModel({ model: 'gemini-1.5-pro' }); const { prompt } = await req.json(); const result = await model.generateContent(prompt); return Response.json({ text: result.response.text() }); } `

4. Transition to Vertex AI for Enterprise Access If your business is located in a country where Google AI Studio's developer API is restricted, you should migrate your SDK integration to Google Cloud Vertex AI. Vertex AI offers broader enterprise availability and different regional residency options.

1. Enable the Vertex AI API in your Google Cloud Platform (GCP) Console. 2. Install the Vertex AI SDK for your language (e.g., @google-cloud/vertexai for Node.js). 3. Initialize the SDK by explicitly defining a supported GCP region: `javascript const { VertexAI } = require('@google-cloud/vertexai'); const vertexAI = new VertexAI({ project: 'your-gcp-project-id', location: 'us-central1' }); ` This routes your requests directly through the designated Google Cloud data center, bypassing local IP location checks.

When to escalate If your server is physically located in a supported region (such as the United States or Western Europe) but you still receive the location error, your ISP or cloud provider may have misconfigured IP geolocation databases.

Check if your network is routing traffic over an active corporate VPN or IPv6 tunnel that misrepresents your true location. If the issue persists on a verified, supported network, search the Google AI Developer Forum or file a bug report in the public Google Issue Tracker with your server's public IP range.