Gemini API Skill for RunAPI

Configure Gemini or OpenAI-compatible clients to use Gemini models on RunAPI.

Model Reference · Skill Repo · All Models

Call the Gemini API through RunAPI with either the OpenAI SDK or the native Gemini protocol — point any OpenAI-compatible client at https://runapi.ai/v1beta/openai, send gemini-2.5-flash, gemini-2.5-pro, gemini-3-flash-preview, gemini-3-pro-preview, or gemini-3.1-pro-preview, and pay through one RunAPI balance. This skill teaches Claude Code, Codex, Gemini CLI, Cursor, and 50+ agents how to wire a Gemini API client up against RunAPI.

The canonical agent file is skills/gemini/SKILL.md.

Install the skill

npx skills add runapi-ai/gemini -g

Or paste this prompt to your AI agent:

Install the gemini skill for me:

1. Clone https://github.com/runapi-ai/gemini
2. Copy the skills/gemini/ directory into your
   user-level skills directory (e.g. ~/.claude/skills/
   for Claude Code, ~/.codex/skills/ for Codex).
3. Verify that SKILL.md is present.
4. Confirm the install path when done.

Use the Gemini API on RunAPI

The Gemini API on RunAPI exposes two protocols:

1. OpenAI-compatible — POST /v1beta/openai/chat/completions. Drop-in for any existing OpenAI SDK client.
2. Native Gemini — POST /v1beta/models/<model>:streamGenerateContent (currently gemini-3-flash-preview). Drop-in for the official Google Generative AI SDK.

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_RUNAPI_TOKEN",
    base_url="https://runapi.ai/v1beta/openai",
)

response = client.chat.completions.create(
    model="gemini-2.5-flash",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "YOUR_RUNAPI_TOKEN",
  baseURL: "https://runapi.ai/v1beta/openai",
});

const response = await client.chat.completions.create({
  model: "gemini-2.5-flash",
  messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);

curl -X POST "https://runapi.ai/v1beta/openai/chat/completions" \
  -H "x-api-key: YOUR_RUNAPI_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-2.5-flash",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Get a RunAPI API Key at https://runapi.ai/api_keys.

Connect Gemini CLI itself

export GOOGLE_API_KEY=YOUR_RUNAPI_TOKEN
export GOOGLE_GENAI_BASE_URL=https://runapi.ai
gemini

Supported Gemini models

Model ID	Endpoint
gemini-2.5-flash	/v1beta/openai/chat/completions
gemini-2.5-pro	/v1beta/openai/chat/completions
gemini-3.1-pro-preview	/v1beta/openai/chat/completions
gemini-3-pro-preview	/v1beta/openai/chat/completions
gemini-3-flash-preview	OpenAI or native :streamGenerateContent

gemini-flash-latest is an alias for gemini-3-flash-preview.

Routing

• Gemini API on RunAPI: https://runapi.ai/models/gemini
• Gemini API docs: https://runapi.ai/docs#gemini
• Provider page: https://runapi.ai/providers/google
• Browse the full RunAPI catalog: https://runapi.ai/models
• Skill repository: https://github.com/runapi-ai/gemini

Agent rules

• Keep API keys in GOOGLE_API_KEY / OPENAI_API_KEY (or your secret manager); never inline them in commits or shell history.
• Stream long responses (stream: true) so the agent can release the terminal/IO loop early.
• For pricing, rate-limit, and commercial-usage answers, link to https://runapi.ai/models/gemini rather than this README.

License

Licensed under the Apache License, Version 2.0.