Model Rover

One endpoint. Every leading model.

Unified AI model gateway

One key for the models you need

An OpenAI-compatible API that lets one key call GPT, Claude, Gemini, DeepSeek, and other leading models. Pay as you go, integrate in minutes.

Start for freeRead the docs
Tokens a day
100B+
Routed through the gateway

01Unified access

Many models.One integration.

Protocols, credentials, and billing from different providers, behind a single endpoint. Keep the SDKs you know and change only the base URL and API key.

  1. One endpoint

    OpenAI, Anthropic, and Gemini protocols share the same base URL, with no per-provider integration.

  2. One key

    Authentication, routing, and billing are handled in one place, so you don't open and fund an account per provider.

  3. Switch models freely

    Changing models usually means changing the model parameter, so every task gets the right model.

Your applicationA world of models

Connection diagram, not live service status

Familiar protocols. More freedom to choose.

OpenAI / Anthropic / Gemini

See how to connect

02Every modality

Text, image, video, and embeddings,on one platform.

From reasoning and chat to multimodal generation, turn the strengths of different models into your next product capability.

Original AURA portable speaker study, with an aluminium body and woven grille in a carefully lit setting

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.

Explore the API guide

Original visual study · Not a model benchmark

Explore all models

03Reliability

Upstreams fluctuate.Your service doesn't have to.

The gateway routes every request in real time and switches channels when one fails, so you don't need another layer of retries and failover in your code.

Request trace
Demo data
POST /v1/chat/completionsstream: true
  1. Select channel2 ms
    capabilities · breaker · affinity · priority
  2. Attempt 1 · Channel A118 ms
    503 upstream overloaded → switching
  3. Attempt 2 · Channel B312 ms
    200 · first byte 312 ms
  4. Streaming responseSSE

    Sure. Here are three key points: define the goal, break it into steps, then verify each one.

To your application, this is just a normal streaming response.

  • Smart routing

    Each request goes to a suitable upstream channel based on model capabilities, channel priority, and cost strategy.

  • Automatic failover

    When an upstream times out, rate-limits, or errors, the gateway retries on another available channel before the first byte is returned.

  • Circuit breaking

    Channels that keep failing are isolated temporarily and probed for recovery, so requests stop hitting the same fault.

  • Cache affinity

    Consecutive requests from the same key to the same model stay on the same upstream when possible, so multi-turn chats and agents hit prompt caches more often.

Illustrative only. Channel names and timings are demo data.

04Observable · Controllable

Every callvisible, accountable, and bounded.

Request logs, cost breakdowns, and key limits in one place, ready for production from your first call.

Project overview
Demo data
Request details
/v1/chat/completions
Request IDStatusCost
2000.00504
2000.002952
4290
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
Explore request & usage management

Interactive interface illustration. All requests, charges and limits are demo data.

05Quickstart

Three stepsto your first call.

Create an API key, choose a model, and send a streaming request with an SDK you already know.

  1. 01Create an API key
  2. 02Choose a model and protocol
  3. 03Set base_url and run the example
Get an API keyRead the quickstart

These examples use OpenAI-compatible Chat Completions. See the docs for other protocols and model-specific parameters.

Choose an example model
main.pySDK / SSE
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="YOUR_MODEL_ID",    messages=[{"role": "user", "content": "Hello!"}],    stream=True,) for chunk in stream:    if chunk.choices:        print(chunk.choices[0].delta.content or "", end="", flush=True)
Your key stays on your serverStreaming supported

The model catalog is unavailable. Replace YOUR_MODEL_ID with a published language model ID.

06FAQ

Before you start,you may want to know.

Key rules for protocol compatibility, billing, and data retention. See the developer docs for details.

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

Spend your time on the product.Leave integration to the gateway.

Create an API key, set base_url, and start calling. Pay for actual usage, with no account to open per provider.

Get an API keyRead the docs

API endpointhttp://127.0.0.1:11113/v1