Open-source AI infrastructure
Compare Everstack and LiteLLM on licence terms, which governance features sit in the enterprise directory, runtime scope, and what a migration actually costs.
LiteLLM's root LICENSE states that everything under the enterprise/ directory is governed by a separate licence and everything else is MIT. That directory exists, which is why GitHub reports the repository licence as NOASSERTION. LiteLLM's enterprise page lists virtual keys, budgets, RPM and TPM limits, spend by key, user, team and org, SSO with SCIM, and OIDC or JWT auth. Everstack ships those under Apache-2.0.
LiteLLM describes itself as calling 100+ LLM APIs, and it has 57,637 GitHub stars with commits landing daily. Everstack's provider coverage is narrower. If your model list includes something niche, check it before anything else, because this can settle the evaluation on its own.
LiteLLM routes model traffic. Agent sessions, isolated code execution, vector memory, workflows, evaluations and human review are separate systems you choose and operate. Everstack runs those on the same control plane, so a trace follows the work rather than stopping at the request boundary.
Both terminate an OpenAI-compatible request, so applications move with a base URL and key change. The real work is re-expressing proxy configuration, and rewriting anything that imports the litellm Python SDK directly rather than calling the proxy over HTTP.