VARIANTE · Google / Gemini

Gemini gemini-2.5-flash API

A model variant exposed through RunAPI's unified AI API.

Operational · text · Commercial use supported

# Works with Claude Code, Codex, Gemini CLI, Cursor, and 50+ agents
npx skills add runapi-ai/gemini -g

The -g flag installs globally so every project picks it up.

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.

Switch variant

gemini-2.5-pro gemini-3-flash-preview gemini-3-pro-preview gemini-3.1-pro-preview gemini-3.5-flash

RESUMEN

Gemini gemini-2.5-flash is available through the same RunAPI auth, SDKs, and agent skill workflow.

Unified endpoint
SDK snippets
Agent install path
Las generaciones fallidas no se cobran

PRECIOS

Las generaciones fallidas no se cobran

Chat completion

Input $0.15 / 1M tokens

Output $1.25 / 1M tokens

FICHA TÉCNICA

Model ID	gemini-2.5-flash
Proveedor	Google
Modalidad	text
Task type	synchronous
Facturación	1K tokens
Endpoint	/v1/chat/completions
Commercial	Yes
Status	Operational

INICIO RÁPIDO

Quickstart — gemini-2.5-flash

runapi.ai

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."}]
)

@runapi.ai/gemini v1

CÓMO FUNCIONA