LiteLLM vs Kong AI Gateway
Both are self-hostable and both are open-core. The line that actually decides it: is your gateway an LLM gateway, or a general API gateway that also speaks to models?
LiteLLM and Kong AI Gateway get compared because they are the two self-hostable options most teams shortlist. They are not the same kind of software. LiteLLM is an LLM proxy — its whole surface is models, providers and OpenAI-compatible routing. Kong is a general API gateway (plugins, upstreams, rate limiting for arbitrary HTTP traffic) with AI plugins added. That difference drives every other row below: protocol entrypoints, governance granularity, and how much you have to build yourself.
Three gateways, five criteria
Each of the first two columns is a one-line read of the corresponding comparison page. The GateLLM column is our own position, not a third-party assessment — weigh it accordingly.
| Criterion | LiteLLM | Kong AI Gateway | GateLLM |
|---|---|---|---|
| Deployment | Self-hosted OSS | Self-hosted OSS (+ managed Konnect) | Fully self-hosted (Docker / Helm), no vendor control plane |
| Billing anchor | Free OSS; Enterprise usage-priced | Free OSS; Enterprise-gated plugins | Per-instance license; no token markup, no per-seat fee |
| Protocol entrypoints | OpenAI-centric | OpenAI-compatible + AI plugins | Four ingress x four egress (OpenAI / Anthropic / Gemini / DashScope) |
| Governance | SSO (5-user cap) / RBAC in Enterprise | RBAC / SSO in Enterprise | SSO / SCIM / RBAC + per-key-group ACL and budget caps |
| Vendor independence | Independent (BerriAI) | Independent (Kong Inc.) | Independent (Fluxon LLC) |
When LiteLLM, when Kong, when neither
Choose LiteLLM if the traffic you are governing is model traffic and nothing else: per-model routing, provider fallback and cost attribution without learning a plugin DSL, and you are comfortable operating a Python service. It is the shortest path from "call many providers" to "call many providers through one endpoint".
Choose Kong if you already run Kong for non-LLM API traffic. Reusing the gateway you have — its plugins, its rate limiting, its operational runbooks — usually beats introducing a second gateway just for AI. The AI plugins are the smaller half of that decision.
Neither, if a single provider, a single team and a manageable monthly bill are your actual situation. Calling the provider API directly is simpler than either option, and no gateway earns its operational cost until you need multi-provider failover, per-team cost attribution, or compliance controls the provider cannot give you.