Learn how Bifrost 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
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Last 30 days
Last commit
Repository age
Version
Self-hosted
Repository

Both Bifrost 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 Bifrost in community adoption with 56,760 stars compared to 7,431 stars on GitHub. This 7.6x difference suggests LiteLLM has a much larger and more active community. In terms of developer contributions, LiteLLM has 10,723 forks, indicating strong developer engagement.
Bifrost is growing faster, adding 800 stars in the last 30 days (+12%) against adding 2,635 stars for LiteLLM (+4.9%). Bifrost is the smaller project of the two, so it is closing the gap rather than extending a lead.
Both projects show recent activity, with Bifrost last updated 7 hours ago and LiteLLM 7 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: Bifrost uses Golang, Rust while LiteLLM leverages Next.js.
LiteLLM has been in development longer, starting 3 years ago, compared to Bifrost which began 1 year ago. This 1.7-year head start suggests LiteLLM may have more mature features and established processes.
Bifrost 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 Bifrost may be primarily cloud-based or require different deployment approaches.