AI Gateway vs LiteLLM
Side-by-side comparison of two AI agent tools
Short answer
- LiteLLM is growing faster: +2,982 GitHub stars in the last 30 days vs +323 for AI Gateway.
- Pick AI Gateway for: a blazing fast AI Gateway with integrated guardrails. Pick LiteLLM for: open-source Python SDK and AI gateway for calling 100+ LLMs through a unified OpenAI-compatible interface.
From GitHub data refreshed daily.
AI Gatewayopen-source
A blazing fast AI Gateway with integrated guardrails. Route to 200+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.
LiteLLMfree
Open-source Python SDK and AI gateway for calling 100+ LLMs through a unified OpenAI-compatible interface
Metrics
| AI Gateway | LiteLLM | |
|---|---|---|
| Stars | 13.1k | 60.1k |
| Star velocity /mo | 323.36842105263156 | 3.0k |
| Commits (90d) | 0 | 13.2k |
| Releases (6m) | 0 | 10 |
| Downloads (30d, npm + PyPI) | 1.9K | — |
| Overall score | 0.3390945209311889 | 0.9321427193766948 |
Pros
- +支持1600+模型的大规模路由能力，覆盖主流AI提供商
- +超高性能表现：<1ms延迟，122kb轻量级架构，日处理100亿tokens验证
- +企业级可靠性：自动重试、故障转移、负载均衡等生产环境必需功能
- +统一API接口设计，一套代码兼容100多个不同的LLM提供商，大幅简化多模型切换和对比测试
- +内置企业级功能如成本追踪、负载均衡、安全防护栏，为生产环境提供完整的AI治理解决方案
- +既提供Python SDK又提供独立的代理服务器部署模式，适合不同规模和架构的项目需求
Cons
- -企业级功能可能对简单用例过于复杂
- -文档信息不完整，可能存在学习曲线
- -高级配置和企业部署可能需要技术专业知识
- -作为中间层抽象，可能无法完全利用某些模型提供商的独特功能和高级参数配置
- -依赖网络连接和第三方API稳定性，增加了系统的复杂度和潜在故障点
- -对于简单的单模型应用场景可能存在过度设计，增加不必要的依赖和学习成本
Use Cases
- •多模型AI应用需要统一API接口和智能路由选择
- •企业级AI服务要求高可用性、自动故障转移和负载均衡
- •大规模AI应用需要成本优化和性能监控的网关层
- •AI应用开发中需要对比测试多个LLM模型性能，快速切换不同提供商而无需重写代码
- •企业级AI服务需要统一的成本监控、访问控制和负载均衡管理多个模型调用
- •构建AI代理或聊天机器人时需要根据用户需求和成本考虑动态选择最适合的模型
FAQ
- Which is more popular, AI Gateway or LiteLLM?
- LiteLLM has more GitHub stars (60,079 vs 13,121).
- Which is more actively developed, AI Gateway or LiteLLM?
- LiteLLM had more commits in the last 90 days (13,238 vs 0).
- Should I use AI Gateway or LiteLLM?
- Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.