Quickstart

1. Create an API key

Sign in to the Modelflare console, open API Keys, and create a key. Choose a non-default group that lists the model you want to call.

Keep the key ready. Do not put it in client-side code or a public repository.

2. Send a first request

The OpenAI-compatible Chat Completions endpoint is:

POSThttps://modelflare.dev/v1/chat/completions

cURL

bash

curl https://modelflare.dev/v1/chat/completions \
  -H "Authorization: Bearer YOUR_MODELFLARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.6-sol",
    "messages": [
      {"role": "user", "content": "Hello"}
    ]
  }'

Python

Python

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_MODELFLARE_API_KEY",
    base_url="https://modelflare.dev/v1",
)

response = client.chat.completions.create(
    model="gpt-5.6-sol",
    messages=[{"role": "user", "content": "Hello"}],
)

print(response.choices[0].message.content)

Node.js

JavaScript

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "YOUR_MODELFLARE_API_KEY",
  baseURL: "https://modelflare.dev/v1",
});

const response = await client.chat.completions.create({
  model: "gpt-5.6-sol",
  messages: [{ role: "user", content: "Hello" }],
});

console.log(response.choices[0].message.content);

Replace gpt-5.6-sol with a model your key can access. The live catalog is on Models & Pricing.

3. Pick the right surface next

• Coding agents: Codex, Claude Code, Grok Build
• Image models: Image models
• Video models: Video models
• Agent workflow: Media Skill
• Which family to call: Which endpoint to call