Gemini
Google's multimodal LLM for chat, code generation, reasoning, and long-context tasks.
# Works with Claude Code, Codex, Gemini CLI, Cursor, and 50+ agents
npx skills add runapi-ai/gemini -gInstall 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.
Gemini is Google's multimodal large language model family supporting text, image, audio, and code understanding. Available in Flash and Pro variants, it handles tasks from quick summarization to deep reasoning and complex coding.
- Installable agent skill
- Unified API key
- SDK examples included
- Fehlgeschlagene Generierungen werden nicht berechnet
Varianten
Use this model from your agent
# User prompt to the agent
"Analyze this codebase and suggest three performance improvements with before/after examples."// Code generated by the agent via @runapi.ai/gemini
import { GeminiClient } from '@runapi.ai/gemini';
const client = new GeminiClient();
const result = await client.chatCompletion.run({
model: 'gemini-2.5-flash',
prompt: 'Analyze this codebase and suggest three performance improvements with before/after examples.',
});How to call this model
Install the skill
Add the model skill to your agent or install the SDK package.
Authenticate once
Use your RunAPI key for every supported model.
Send a request
Use the unified schema for the endpoint you need.
Receive output
Poll by task ID or handle the callback when the generation completes.
SDK quickstart
curl -X POST https://runapi.ai/v1/chat/completions \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-2.5-flash",
"messages": [
{
"role": "user",
"content": "Analyze this codebase and suggest three performance improvements with before/after examples."
}
]
}'import { GeminiClient } from "@runapi.ai/gemini";
const client = new GeminiClient();
const result = await client.chatCompletion.run({
model: "gemini-2.5-flash",
messages: [{"role":"user","content":"Analyze this codebase and suggest three performance improvements with before/after examples."}],
});require "runapi/gemini"
client = RunApi::Gemini::Client.new
result = client.chat_completion.run(
model: "gemini-2.5-flash",
messages: [{role: "user", content: "Analyze this codebase and suggest three performance improvements with before/after examples."}]
)Where Gemini fits
Gemini is Google's flagship multimodal LLM, available in Flash (fast) and Pro (frontier reasoning) variants. Through RunAPI, all Gemini models share the same API shape and billing.
Why use Gemini through RunAPI
One API key
Use the same credentials across models and providers.
Agent-ready
Installable skills include docs and schema for tool calls.
Predictable billing
Usage-based pricing is visible before you call.
Frequently asked questions
How do I call this model?
Use the RunAPI SDK, CLI, or REST endpoint shown on this page.
Do failed generations cost money?
Fehlgeschlagene Generierungen werden nicht berechnet
Can agents use it directly?
Yes. Install the model skill and your agent gets the docs, schema, and examples.
