Overview

ModelGo Overview

ModelGo is a production-ready AI model gateway. With one API key and a unified API, you can call text, image, video, audio, embedding, and reranking models without maintaining separate integrations for each model.

Whether you are evaluating models, building AI features, or taking model calls to production, you can use the same development workflow and manage permissions, usage, logs, and security policies in one platform.

One API for Multiple Models

ModelGo brings different model capabilities into a single development workflow. Choose the capability that fits your use case, then open the detailed documentation for endpoints, parameters, and request examples.

Model categoryCapabilitiesDocumentation
TextConversations, content generation, reasoning, and tool useText Generation
ImagesGenerate images from text or edit existing imagesImage Generation · Image Edits
VideoGenerate videos and track progress and results through async tasksStandard Video API · Async Tasks
EmbeddingsGenerate text or multimodal embeddings for semantic search and RAGEmbeddings
AudioText to speech, speech to text, and speech translationSpeech · MiniMax Audio · Transcriptions · Translations
RerankReorder candidate results to improve retrieval quality in search and RAGRerank

You can also browse available models in the Model Catalog, test them in the Model Playground, or call GET /v1/models to list the models available to the current API key.

Use Familiar Protocols and Tools

ModelGo supports both OpenAI and Anthropic text protocols. If your project already uses their SDKs or compatible clients, you can usually keep your existing integration and replace only the Base URL and API key.

Choose the Base URL that matches your client protocol:

OpenAIhttps://api.modelgo.ai/v1
Anthropichttps://api.modelgo.ai

All requests use the same ModelGo API key for authentication. Create an API key in the console, then see Authentication for request headers and security guidance.

Built for Production Calls

ModelGo provides the controls needed when model calls move into production, not just a unified endpoint:

  • Reliable calls: Handle routing and failover at the gateway layer to reduce the impact of a single path failure.
  • Permissions and security: Define access through workspaces, members, and API keys, with controls for budgets, available models, and request sources.
  • Usage and cost: Review request counts, token usage, and spend by time, workspace, model, member, and API key.
  • Call tracing: Use request IDs, status, latency, and error details to troubleshoot synchronous calls and asynchronous tasks.

Get Started

If this is your first ModelGo integration, follow these steps: