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LiteLLM is an open-source framework that lets developers use 100+ AI models through a single OpenAI-format API, simplifying model switching and cost control.
LiteLLM is an open-source developer tool designed to simplify working with multiple large language models (LLMs) through a single, unified API format. Instead of rewriting code for each provider, developers can use the OpenAI-compatible message structure once and switch between models such as GPT-4o, Claude, Llama, or local models by changing only the model name.
Key Facts
- LiteLLM allows developers to use a single OpenAI-style API format.
- Supports 100+ language models across cloud and local providers.
- Model switching requires only changing the model identifier.
- Includes features like cost tracking and automatic fallback handling.
Main Development
As AI adoption accelerates in 2026, developers increasingly face the challenge of integrating multiple LLM providers, each with different API structures and authentication methods. LiteLLM addresses this by acting as a compatibility layer. Developers write their code once using the OpenAI message format, then route requests to different models without restructuring prompts or modifying message schemas.
This architecture enables teams to experiment with different models — from GPT-based systems to Anthropic’s Claude, Meta’s Llama, or even local deployments — without major code refactoring. LiteLLM can also function as a centralized hub for managing multiple AI services simultaneously.
How to Use LiteLLM
To use LiteLLM, developers first integrate the LiteLLM library into their project environment. They then write API calls using the standard OpenAI-compatible format for messages and completions. When switching models, the only required change is updating the model parameter to the desired provider (e.g., from “gpt-4o” to “claude” or a local model name).
LiteLLM can also be configured to manage cost limits, apply automatic fallbacks if a provider fails, and route requests across multiple LLM endpoints. This makes it particularly useful for production systems that rely on more than one AI model provider.
Why Developers Are Adopting It
By removing the need to learn and maintain multiple APIs, LiteLLM reduces development time and complexity. For teams building AI-powered applications, the framework offers flexibility, provider independence, and operational control — key advantages as the AI model ecosystem continues to expand.
