01Less integration. More creation.
Many models. One simpler connection.
Bring scattered model services into one platform. Less integration to maintain. More product to build.
Leave fragmented access behind
Stop managing separate credentials, protocols and accounts for every provider.
Connect through one gateway
A shared credential brings authentication, channel routing and usage management together.
Keep your options open
Choose models for the task and keep building with supported protocols.
Connection diagram, not live service status
Familiar protocols. More freedom to choose.
OpenAI / Anthropic / Gemini
02From capability to possibility
Not just more models. More ways to build.
Understand, create, retrieve. Turn the strengths of different models into your next product capability.
Images / API
Give an idea its shape.
From one product image to an entire visual direction, connect image generation and editing to your creative workflow.
Explore models for this capability
No published models are currently shown in this category. The guide explains how integration works.
Public price for one meter. Full pricing conditions are on the model page.
Original visual study · Not a model benchmark
03Designed for what comes next
Beyond the first call. In control of every one.
See what happened, understand what it cost, and set clear boundaries for every part of your product.
/v1/chat/completions| Request ID | Status | Cost |
|---|---|---|
| 200 | 0.00504 | |
| 200 | 0.002952 | |
| 429 | 0 |
- First token
- 248 ms
- Input tokens
- 1,240
- Output tokens
- 320
One request. The complete picture.
Status, first-token latency, usage and a request ID in one place. Investigate without jumping between provider dashboards.
- Model
- Demo language model
- Status
- Succeeded
- Request total
- 0.00504 credits
Interactive interface illustration. All requests, charges and limits are demo data.
04For the builders
Your idea. Your first API call.
Choose a model, configure your endpoint and credentials, and start building with a familiar protocol.
- 01Get an API key
- 02Choose a model and protocol
- 03Run your first request
These examples use OpenAI-compatible Chat Completions. See the docs for other protocols and model-specific parameters.
from os import environfrom openai import OpenAI client = OpenAI( base_url="http://127.0.0.1:11113/v1", api_key=environ["API_KEY"],) stream = client.chat.completions.create( model="openai/gpt-5.6-luna", messages=[{"role": "user", "content": "Hello!"}], stream=True,) for chunk in stream: if chunk.choices: print(chunk.choices[0].delta.content or "", end="", flush=True)Install the SDK for your language and set API_KEY in your server environment first.
05Before you begin
Your next integration. Not another system to build.
Make the connection simpler. Keep your focus on the product you actually want to create.
The platform supports client protocols including OpenAI, Anthropic and Gemini. For a supported protocol, keep the corresponding SDK and change the endpoint, API key and model ID. Each model's capabilities and parameter support are documented separately.
Read the full guide