Gemini API key

A Gemini API key authenticates your calls to Google's Gemini models. You can get one directly from Google AI Studio, or use a single sk-kunavo- key that reaches Gemini through the same OpenAI-compatible API you already use for everything else.

What a Gemini API key is

A Gemini API key is a bearer credential that authorizes requests to Google's Gemini family. Every request carries the key in an Authorization header; the platform meters usage against it and bills per token. On Kunavo today that means gemini-2-5-pro and gemini-2-5-flash, called through the OpenAI-compatible endpoint.

There are two ways to obtain a working key, depending on whether you want Gemini alone or Gemini alongside the other frontier models.

Option A — a key direct from Google AI Studio

1. Go to aistudio.google.com and sign in with a Google account.
2. Open Get API key → Create API key. Keys look like AIza....
3. For production volume, attach the key to a Google Cloud project with billing enabled.

This is the right path if Gemini is the only model you will ever call. If you also use Claude, image or video models, you would end up managing a separate key, SDK and invoice per provider.

Option B — one Kunavo key for Gemini and everything else

Kunavo fronts Gemini behind an OpenAI-compatible API. One sk-kunavo- key reaches Gemini and every other model, with a single Stripe-billed balance.

1. Create a Kunavo account — you get $2 of free credit.
2. Generate a key at /app/keys. It is shown once; store it in an environment variable.
3. Point the OpenAI SDK at https://api.kunavo.com/v1 and call a Gemini slug.

Call Gemini with Python

Keep the official OpenAI SDK. Change base_url and the model name — nothing else.

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["KUNAVO_API_KEY"],
    base_url="https://api.kunavo.com/v1",  # the only line that changes
)

resp = client.chat.completions.create(
    model="gemini-2-5-flash",
    messages=[{"role": "user", "content": "Summarize the plot of Dune in two sentences."}],
)
print(resp.choices[0].message.content)

Call Gemini with Node.js

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.KUNAVO_API_KEY,
  baseURL: "https://api.kunavo.com/v1",
});

const resp = await client.chat.completions.create({
  model: "gemini-2-5-flash",
  messages: [{ role: "user", content: "Summarize the plot of Dune in two sentences." }],
});
console.log(resp.choices[0].message.content);

Or call it with curl

curl https://api.kunavo.com/v1/chat/completions \
  -H "Authorization: Bearer $KUNAVO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-2-5-flash",
    "messages": [{"role": "user", "content": "Hello, Gemini"}]
  }'

Which Gemini model to use

• gemini-2-5-flash — fast, extremely inexpensive default for chat, extraction and summarization.
• gemini-2-5-pro — stronger reasoning, vision and long-context analysis.

Security checklist

• Never expose a key client-side. Browser and mobile bundles are public — always proxy through your own server.
• Use one key per project or environment so a leak can be revoked without taking down everything else.
• Rotate quarterly. Kunavo allows multiple live keys, so rotation is a clean overlap rather than a hard cutover.
• Watch /app/usage for unexpected traffic broken down by key.

FAQ

Where to go next

• Quickstart — your first request in 60 seconds
• Gemini API pricing 2026
• Browse the full model catalog