Verdict

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Best if
You are platform engineers and need: Giving developers access to multiple LLMs
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LiteLLM: LLM Gateway for managing and accessing 100+ LLMs in OpenAI format

Overview

LiteLLM is an LLM Gateway (OpenAI Proxy) designed to manage authentication, load balancing, and spend tracking across 100+ LLMs, all while maintaining the OpenAI format. It simplifies the process of using LLM APIs from various providers like OpenAI, Azure, Cohere, Anthropic, Replicate, and Google. LiteLLM offers consistent outputs and exceptions for all LLM APIs, along with logging and error tracking for all models. It provides features like cost tracking, batches API, guardrails, model access, budgets, LLM observability, rate limiting, prompt management, S3 logging, and pass-through endpoints.

liteLLM screenshot

Best for

Short scenarios where liteLLM tends to shine.

  • Giving developers access to multiple LLMs

    Best for Platform engineers

  • Managing spend across different LLM providers

    Best for MLOps engineers

  • Implementing LLM fallbacks for reliability

    Best for Software developers

  • Standardizing LLM API access across an organization

    Best for AI product managers

How it works

Use LiteLLM by calling LLM APIs using the chatGPT format - completion(model, messages). It provides consistent outputs and exceptions for all LLM APIs. You can deploy LiteLLM open source or try LiteLLM Enterprise for more features.

Example outputs 1

Sample generations and before/after results for liteLLM.

Access & connections

Where you can use liteLLM.

Platforms

Web

Capabilities

What this tool accepts, produces, and is strongest at.

Highlights

  • LLM Gateway for 100+ LLMs
  • OpenAI-compatible API
  • Cost Tracking and Budget Management
  • LLM Fallbacks
  • Load Balancing
  • Rate Limiting
  • Prompt Management
  • Logging and Error Tracking

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In the news

Launch coverage and community mentions for liteLLM.

FAQ 5

What is LiteLLM?
LiteLLM is an LLM Gateway (OpenAI Proxy) designed to manage authentication, load balancing, and spend tracking across 100+ LLMs, all while maintaining the OpenAI format. It simplifies the process of using LLM APIs from various providers like OpenAI, Azure, Cohere, Anthropic, Replicate, and Google. LiteLLM offers consistent outputs and exceptions for all LLM APIs, along with logging and error tracking for all models. It provides features like cost tracking, batches API, guardrails, model access, budgets, LLM observability, rate limiting, prompt management, S3 logging, and pass-through endpoints.
How to use LiteLLM?
Use LiteLLM by calling LLM APIs using the chatGPT format - completion(model, messages). It provides consistent outputs and exceptions for all LLM APIs. You can deploy LiteLLM open source or try LiteLLM Enterprise for more features.
What is LiteLLM?
LiteLLM simplifies model access, spend tracking, and fallbacks across 100+ LLMs.
What features does LiteLLM offer?
LiteLLM offers features like cost tracking, budgets, rate limits, OpenAI-compatible API, LLM fallbacks, and more.
How does LiteLLM help with LLM management?
LiteLLM standardizes logging, the OpenAI API, and authentication for all models, significantly reducing operational complexities.
liteLLM