# Apertis vs LiteLLM: managed control plane or self-hosted proxy

Compare Apertis's managed workspace with LiteLLM's open-source proxy and enterprise options by infrastructure ownership, control needs, and evidence burden.

Canonical: https://apertis.ai/compare/litellm

## Decision intent

You want a compatible multi-provider layer and need to decide whether your team should operate the proxy or consume a managed gateway workspace.

## Decision table

| Question | Apertis | LiteLLM |
| --- | --- | --- |
| Control boundary | **Managed keys, model policy, quota, Activity, and billing context.** | Virtual keys, budgets, fallback, and logging are published proxy capabilities. |
| Upstream keys | **Apertis holds the upstream provider credentials; your team issues bounded workspace tokens, each with its own quota.** | You configure each upstream provider key in the proxy you run, and front them with virtual keys. |
| Routing decision | **Channel selection follows declared policy — user group, model availability, and channel priority.** | Routing is whatever your own proxy configuration declares. |
| Verify before migration | **Check the response and managed Activity trail.** | Test deployment, database, secrets, upgrades, and observability in your own environment. |
| Spend and limits | Quota is enforced per token, and every call lands in the workspace Activity record. | Budgets and rate limits per virtual key or user, with spend tracking and an admin UI. |
| Primary job | Consume a managed gateway and workspace control surface. | Run or deploy a compatible proxy across supported providers. |
| Infrastructure owner | Apertis operates the gateway product; your team owns workload configuration and policy decisions. | Your team can self-host the open-source proxy or evaluate LiteLLM enterprise options. |

Bold follows the full comparison’s strongest-fit verdict. An unmarked row makes no additional ranking between these two platforms.

## Fit, not winner

### Choose Apertis when

Choose Apertis when you want the gateway, catalog, key boundary, policy, usage, and billing context operated as one managed product.

### Choose LiteLLM when

Choose LiteLLM when self-hosting and owning the proxy runtime is a requirement, or when its current enterprise deployment model matches your infrastructure boundary.

## Migration path

1. **Price the ownership model** — Include runtime, database, upgrades, security response, observability, and on-call work—not only model usage.
2. **Map compatibility assumptions** — List the providers, endpoints, parameters, and fallback semantics the workload actually uses.
3. **Test failure handling** — Exercise timeout, rate-limit, authentication, and provider failure paths in a non-production environment.
4. **Keep a rollback boundary** — Move one workload first and preserve a controlled return path until requests and records match expectations.

## Primary sources

These links are evidence inputs, not endorsements. The LiteLLM cells in the decision table were read from them on 2026-09-07; product details can change after that.

- [LiteLLM pricing](https://www.litellm.ai/pricing): Current open-source and enterprise positioning.
- [LiteLLM proxy quickstart](https://docs.litellm.ai/docs/proxy/docker_quick_start): Current self-hosted proxy setup.
- [LiteLLM proxy docs](https://docs.litellm.ai/docs/simple_proxy): Current proxy capabilities and configuration.

## Next action

Run one representative request against gpt-5.5 and inspect the resulting workspace record before migrating more.