Using Google Gemini With Kilo Code

Kilo Code supports Google's Gemini family of models through the Google AI Gemini API.

Website: https://ai.google.dev/

Getting an API Key

1. Go to Google AI Studio: Navigate to https://ai.google.dev/.
2. Sign In: Sign in with your Google account.
3. Create API Key: Click on "Create API key" in the left-hand menu.
4. Copy API Key: Copy the generated API key.

Configuration in Kilo Code

{% tabs %} {% tab label="VSCode (Legacy)" %}

1. Open Kilo Code Settings: Click the gear icon ({% codicon name="gear" /%}) in the Kilo Code panel.
2. Select Provider: Choose "Google Gemini" from the "API Provider" dropdown.
3. Enter API Key: Paste your Gemini API key into the "Gemini API Key" field.
4. Select Model: Choose your desired Gemini model from the "Model" dropdown.

{% /tab %} {% tab label="VSCode" %}

Open Settings (gear icon) and go to the Providers tab to add Google Gemini and enter your API key.

The extension stores this in your kilo.json config file. You can also edit the config file directly — see the CLI tab for the file format.

{% /tab %} {% tab label="CLI" %}

Set the API key as an environment variable or configure it in your kilo.json config file:

Environment variable:

export GOOGLE_GENERATIVE_AI_API_KEY="your-api-key"

Config file (~/.config/kilo/kilo.json or ./kilo.json):

{
  "provider": {
    "google": {
      "env": ["GOOGLE_GENERATIVE_AI_API_KEY"],
    },
  },
}

Then set your default model:

{
  "model": "google/gemini-2.5-pro",
}

{% /tab %} {% /tabs %}

Tips and Notes

• Pricing: Gemini API usage is priced based on input and output tokens. Refer to the Gemini pricing page for detailed information.
• Codebase Indexing: The gemini-embedding-001 model is specifically supported for codebase indexing, providing high-quality embeddings for semantic code search.