Gatekeeper vs. LiteLLM: Proxy vs. Control Plane
LiteLLM is great for proxying. Gatekeeper is a control plane. That distinction sounds subtle — but it determines whether you need to write your own budget enforcement, RBAC, and audit logging, or whether you get all of that for free.
What They Share
Both LiteLLM and Gatekeeper are open-source HTTP proxies that sit between your application and AI provider APIs. Both support 100+ models. Both translate between OpenAI-format and provider-specific formats. Both can be self-hosted.
If you need "one endpoint to route requests to multiple models" — both work. The question is what comes after that.
The Control Plane Difference
LiteLLM's core is a proxy. It routes requests and handles format translation well. RBAC, budget enforcement, and team management exist in LiteLLM Enterprise — a paid tier with contact-sales pricing.
Gatekeeper's core is a control plane. RBAC, budgets, virtual keys, usage analytics, and audit logging are not add-ons — they are the product. The proxy functionality (format translation, routing) is the foundation, not the ceiling.
The practical difference
With LiteLLM open-source: you get routing. You write your own budget tracking, key management, and usage dashboard.
With Gatekeeper: you get routing plus all of the above, open-source, day one.
Feature Comparison
| Feature | Gatekeeper | LiteLLM |
|---|---|---|
| Model routing (100+ models) | ||
| OpenAI-compatible endpoint | ||
| Anthropic-compatible endpoint | ||
| Streaming support | ||
| Self-hosted | ||
| Virtual API keysLiteLLM requires Enterprise plan | Enterprise | |
| Per-key budget limits | Enterprise | |
| Per-team budgets | Enterprise | |
| RBAC (roles per team)LiteLLM Enterprise: Contact sales | Enterprise | |
| Usage dashboard (built-in) | Enterprise | |
| Audit logs | Enterprise | |
| Semantic caching | ||
| Model fallback / retry | ||
| Prompt logging (off by default) | ||
| Open-sourceBoth Apache 2.0 licensed |
RBAC: Included vs. Contact Sales
This is the sharpest difference. Gatekeeper's RBAC model (Organization → Team → Virtual Key) is available on the free, self-hosted deployment. You can create separate teams for engineering, marketing, and support — each with their own model allowlists and budgets — without paying a per-seat enterprise fee.
LiteLLM's team management and RBAC features are in LiteLLM Enterprise. Enterprise pricing requires contacting sales. For many teams, especially early-stage startups with tight AI budgets, "Contact sales for RBAC" means they simply don't implement it.
Self-Hosting: Both Free
Both Gatekeeper and LiteLLM can be self-hosted for free. Both run on Docker. Neither requires a cloud account.
The difference is the dashboard. LiteLLM open-source has a limited dashboard. LiteLLM Enterprise has a full usage dashboard. Gatekeeper open-source includes the full usage dashboard — cost by provider, cost by model, cost by team, per-key breakdowns — without the enterprise tier.
Provider Support
| Provider | Gatekeeper | LiteLLM |
|---|---|---|
| OpenAI | ||
| Anthropic | ||
| Google (Gemini) | ||
| AWS Bedrock | ||
| Azure OpenAI | ||
| Mistral | ||
| Groq | ||
| Cohere | ||
| Ollama (local) | ||
| Together AI |
When to Choose Each
Choose LiteLLM if: you are building a personal project, you need provider support for a very niche provider not yet in Gatekeeper, or you are already deep in the LiteLLM ecosystem.
Choose Gatekeeper if: you have a team that needs budget controls, you need RBAC without enterprise pricing, you want a built-in usage dashboard, or you are running this in production and care about audit logs.