Learn how Envoy AI Gateway and LiteLLM differ in their key features, development activity, technology stack and community adoption, so you can decide which of these ai gateways is best for you.
Last 30 days
Last commit
17 hours agoRepository age
2 yearsVersion
v1.2.1License
Apache-2.0Repository
ai-gateway
Last 30 days
Last commit
5 hours agoRepository age
3 yearsVersion
v1.108.3Self-hosted
YesRepository
berriai/litellm
Both Envoy AI Gateway and LiteLLM have their unique strengths and serve similar purposes effectively. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
LiteLLM significantly outpaces Envoy AI Gateway in community adoption with 62,946 stars compared to 2,371 stars on GitHub. This 26.5x difference suggests LiteLLM has a much larger and more active community. In terms of developer contributions, LiteLLM has 13,128 forks, indicating strong developer engagement.
Envoy AI Gateway is growing faster, adding 161 stars in the last 30 days (+7.3%) against adding 2,048 stars for LiteLLM (+3.4%). Envoy AI Gateway is the smaller project of the two, so it is closing the gap rather than extending a lead.
Both projects show recent activity, with Envoy AI Gateway last updated 17 hours ago and LiteLLM 5 hours ago.
Both tools share common technology foundations, being built with JavaScript, CSS, Bash, Typescript, JSX, Python. However, they differ in their additional technology choices: Envoy AI Gateway uses Golang while LiteLLM leverages Next.js.
LiteLLM has been in development longer, starting 3 years ago, compared to Envoy AI Gateway which began 2 years ago. This 1.3-year head start suggests LiteLLM may have more mature features and established processes.
Envoy AI Gateway is licensed under Apache-2.0, while LiteLLM's license terms are not publicly specified.
Both tools serve similar use cases in AI Gateways.
LiteLLM provides self-hosting options for complete data control and customization, while Envoy AI Gateway may be primarily cloud-based or require different deployment approaches.