Glossary

What Is a Multi-Model API?

A multi-model API provides access to multiple large language models from different providers through a single, unified endpoint.

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Definition

A multi-model API is an abstraction layer that gives you access to models from OpenAI, Anthropic, Google, Meta, and other providers through one API key, one SDK, and one billing system. Instead of integrating each provider separately — managing different auth flows, request formats, streaming protocols, and error handling — you use a single consistent interface. Multi-model APIs are the foundation of modern AI architectures where no single model is optimal for every task.

Why use multiple models

No single LLM is best at everything. GPT-5.2 excels at code and structured output. Claude Sonnet 4.5 leads in writing and nuanced reasoning. Gemini 3 Flash is the fastest for real-time features. DeepSeek V3 offers strong capability at low cost. Using multiple models lets you match each task to the best-fit model, reduce costs by routing simple tasks to cheaper models, and maintain availability through cross-provider failover.

Multi-model API vs. direct provider integration

Direct integration gives you maximum control and minimal latency for a single provider, but creates vendor lock-in and requires separate codepaths for each model. A multi-model API adds a small latency overhead (typically 10-30ms) but eliminates provider-specific code, enables instant model switching, and provides cross-provider features like failover and comparison. For most production applications, the operational simplicity of a unified API outweighs the minimal latency cost.

LLMWise as a multi-model API

LLMWise provides a multi-model API with orchestration on top. Beyond basic unified access, it offers Compare mode (same prompt to multiple models simultaneously), Blend mode (synthesize best parts from multiple models), Judge mode (one model evaluates another), and Mesh failover (automatic fallback on errors). The API uses OpenAI-compatible message format, making migration from single-provider setups straightforward.

How LLMWise implements this

LLMWise gives you five orchestration modes — Chat, Compare, Blend, Judge, and Mesh — with built-in optimization policy, failover routing, and replay lab. No monthly subscription is required and paid credits do not expire.

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Evidence snapshot

What Is a Multi-Model API? concept coverage

Knowledge depth for this concept and direct paths to adjacent terms.

Core sections
3
concept angles covered
Related terms
3
connected topics linked
FAQs
4
common confusion resolved
Term type
Glossary
intro + practical implementation

Common questions

Is a multi-model API the same as an LLM gateway?
They overlap significantly. An LLM gateway is the infrastructure layer that provides unified access, while a multi-model API describes the interface pattern. Most LLM gateways expose a multi-model API. LLMWise is both: it provides a unified API (gateway) with advanced orchestration features (compare, blend, judge) on top.
How hard is it to switch from OpenAI to a multi-model API?
With LLMWise, migration takes about 15 minutes. The API uses OpenAI-compatible message format (role + content), so you keep your existing prompts. Swap the SDK, set your API key, and optionally add routing or failover. Our migration guides cover the process step by step.
What is a multi-model API in AI?
A multi-model API provides access to multiple large language models from different providers through a single endpoint. Instead of integrating OpenAI, Anthropic, and Google separately, you use one API key and one SDK to access all models. LLMWise is an example of a multi-model API with orchestration features like Compare, Blend, and Judge.
Does using a multi-model API add latency?
A well-built multi-model API adds 10-30 milliseconds for routing and forwarding. LLMWise streams responses as they arrive from the provider, so time-to-first-token is nearly identical to calling the provider directly. The reliability and operational benefits far outweigh the minimal latency cost.

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