Comparison

Everstack vs LiteLLM

LiteLLM is the most widely deployed self-hosted AI gateway there is, and its MIT core is genuinely production capable. The two differences worth your time are where the licence line falls, since governance sits in the enterprise directory, and how much of the problem each one solves past the request.

EverstackEverstack
vs
LiteLLMLiteLLM
View pricingRead documentation

What is LiteLLM?

LiteLLM is an open source AI gateway with a Rust core and a Python SDK, calling 100+ LLM APIs in OpenAI or native format with cost tracking, guardrails, load balancing and logging. It has 57,637 GitHub stars as of August 2026. Its root LICENSE places everything outside the enterprise/ directory under MIT, and everything inside it under a separate licence.

Why teams choose Everstack

  • Virtual keys, budgets, per-tenant limits and SSO ship under one Apache-2.0 licence
  • The same control plane runs agents, sandboxes and evaluations, not just the proxy
  • No separately licensed directory to reason about at compliance review

LiteLLM: Strengths & Limitations

Strengths

  • The default answer in this category, and deservedly so: 57,637 GitHub stars as of August 2026, with commits landing daily.
  • The widest provider coverage anywhere. If a model API exists, LiteLLM almost certainly speaks it, and the community adds new ones fast.
  • A Rust core with a Python SDK, so it is both fast and trivially embeddable in Python codebases that already exist.
  • Enormous ecosystem gravity: worked examples, blog posts, Stack Overflow answers and framework integrations that no younger project can match.
  • The MIT core genuinely is production capable on its own. Plenty of teams run it for years without ever talking to sales.

Limitations

  • The licence is split. LiteLLM's root LICENSE states that everything under the enterprise/ directory is governed by a separate licence, and that directory exists in the repository.
  • The enterprise tier is where governance lives: virtual keys, budgets, RPM and TPM limits, spend tracking by key, user, team and org, SSO with SCIM, and OIDC or JWT auth.
  • Enterprise pricing is not published. The site offers a 30 day trial key and a conversation with sales.
  • It is a gateway. Agent sessions, isolated code execution, evaluations and human review happen in systems you assemble separately.

Everstack advantage

One Apache-2.0 licence, no enterprise directoryGovernance included rather than gatedAgent runtime and sandboxes in the same planePublished pricing you can read without a call

The facts, side by side

Licence, deployment model and list price, taken from each vendor's own documentation. Every source is linked at the bottom of this page.

FactEverstackLiteLLM
LicenceApache-2.0 across the repository, including the enterprise modules.Split. The root LICENSE states that content under enterprise/ is licensed by enterprise/LICENSE and everything else is MIT. GitHub reports the repository licence as NOASSERTION for this reason.
Virtual keys, budgets and per-tenant limitsIncluded.Listed on LiteLLM's enterprise page under Governance, alongside spend tracking by key, user, team and org.
SSO and SCIMIncluded.Listed as an enterprise capability, with OIDC and JWT auth.
Published pricingStarter $0, Build $20/month, Scale $100/month, Enterprise custom (August 2026).Not published. The enterprise page offers custom pricing, a 30 day trial key, and a sales conversation (August 2026).
Provider coverageBroad and growing, but smaller than LiteLLM's. This is not a category we claim to lead.The widest in the category, and its own description cites 100+ LLM APIs.
Agent runtime and isolated executionStateful sessions, tools, approvals, child agents, plus Docker, Firecracker and Kubernetes sandboxes.Out of scope. LiteLLM is a gateway and proxy.
Evaluations and human reviewDatasets, scorers, LLM judges and annotation queues included.Out of scope.
Community sizeSmall. LiteLLM wins this comfortably and it is a real advantage.57,637 GitHub stars as of 31 August 2026, pushed the same day.

Licence read from the root LICENSE file in BerriAI/litellm, stars and activity from the GitHub API, and enterprise capabilities from litellm.ai/enterprise, all on 31 August 2026. LiteLLM does not publish enterprise prices, so none are quoted here.

Feature comparison

Direct capability comparison across key dimensions

FeatureEverstackLiteLLM
Gateway
OpenAI-compatible endpoint
Multi-provider routing
Fallback and retries
Semantic caching
Governance
Virtual keys and budgetsEnterprise
Per-key and per-team spend trackingEnterprise
RPM and TPM limitsEnterprise
SSO and SCIMSSO on Enterprise, no SCIMEnterprise
Runtime
Stateful agent sessions
Isolated code execution
Vector memory
Workflows with approvals
Quality
Datasets and evaluation runs
Human annotation queues
Observability
OpenTelemetry-native tracesVia callbacks and integrations
Ecosystem
Provider coverage breadth
Community size and worked examples

The same job, in both products

Working code rather than adjectives. Each snippet follows the quickstart published by the product it belongs to.

Route a chat completion through the gateway

Both terminate an OpenAI-compatible request, so application code is a base URL change either way. This is the part that makes migration cheap in both directions.

Everstack

call.py
from openai import OpenAIimport osclient = OpenAI(    base_url="https://{instance}.{region}.everstack.ai/openai/v1",    api_key=os.environ["EVERSTACK_API_KEY"],)response = client.chat.completions.create(    model="gpt-4o-mini",    messages=[{"role": "user", "content": "Summarise this report"}],)

LiteLLM

call.py
from openai import OpenAIimport osclient = OpenAI(    base_url="http://litellm-proxy:4000",    api_key=os.environ["LITELLM_MASTER_KEY"],)response = client.chat.completions.create(    model="gpt-4o-mini",    messages=[{"role": "user", "content": "Summarise this report"}],)

Key evaluation questions

What to ask when comparing LiteLLM to Everstack

QuestionEverstackLiteLLM
Do virtual keys and budgets need a paid licence?No. They are in the Apache-2.0 build.They appear under Governance on LiteLLM's enterprise page.
Can I read the price before talking to sales?Yes. Starter $0, Build $20, Scale $100 per month.Not for enterprise. The page offers custom pricing and a trial key.
Does it run the agent, or only route its calls?It runs it, including isolated code execution.It routes the calls. The agent runs elsewhere.
Which supports more providers?Fewer. This is LiteLLM's category to win.More, by a wide margin.

Feature-by-feature analysis

Where each product is genuinely stronger, row by row

Where the licence line falls

Everstack wins
Everstack

Apache-2.0 across the repository. Virtual keys, budgets, per-tenant limits and SSO are in the build.

LiteLLM

MIT for the core, with a separate licence over the enterprise/ directory. Governance features are listed on the enterprise page.

Why Everstack

Both are honest about it. The question is whether the features you need sit on your side of the line, and governance is usually the first thing a growing team needs.

Provider coverage

LiteLLM wins
Everstack

Broad, but not the widest, and we do not pretend otherwise.

LiteLLM

The widest in the category. Its own description cites 100+ LLM APIs, and new providers land quickly.

Why LiteLLM

If your model list includes something niche, check it before anything else. This can decide the whole evaluation on its own.

Scope past the request

Everstack wins
Everstack

Agent sessions, isolated sandboxes, memory, workflows and evaluations run on the same control plane and share a trace.

LiteLLM

A gateway. Everything past the request is a separate system you choose, deploy and operate.

Why Everstack

Neither is wrong. It decides whether you are operating one system or four, and whether a trace stops at the request boundary.

Ecosystem and mindshare

LiteLLM wins
Everstack

Young, small community, fewer worked examples.

LiteLLM

57,637 stars and daily commits. When someone asks for a self-hosted LLM proxy, this is the answer they get.

Why LiteLLM

Ecosystem gravity is real and it compounds. This is LiteLLM's most durable advantage over any newer project, including this one.

Moving from LiteLLM to Everstack

LiteLLM and Everstack both terminate an OpenAI-compatible request, so applications move with a base URL and key change. The real work is re-expressing the proxy config, and deciding what to do with anything built against LiteLLM's Python SDK rather than its proxy.

  1. 1

    Move the endpoint

    Change the base URL and API key. Applications calling through the OpenAI SDK need no other edit.

  2. 2

    Re-express model and provider config

    LiteLLM's model_list entries map to Everstack provider routes. Router settings for fallback and retries map to routing policy.

  3. 3

    Recreate keys, budgets and limits

    If you were on LiteLLM enterprise, virtual keys, budgets and RPM or TPM limits map to Everstack API keys and per-tenant limits. If you were on the MIT build, this is where you gain capability rather than port it.

  4. 4

    Run both and compare before cutting over

    Mirror traffic and compare latency, cost totals and error rates for a release or two.

What breaks

  • Code importing the litellm Python SDK directly, rather than calling the proxy, has no drop-in Everstack equivalent and needs rewriting against the OpenAI SDK or the Everstack SDK.
  • LiteLLM custom callbacks and logging integrations do not carry over.
  • Any provider LiteLLM supports that Everstack does not yet will block a full cutover. Check your model list first.

What does not carry over

  • Historical spend and usage records held in the LiteLLM database.
  • Existing virtual key objects and their budget state.
  • Custom router strategies expressed in LiteLLM configuration.

Read this part first

When to choose LiteLLM instead

LiteLLM is the most widely deployed self-hosted AI gateway there is, and for many teams it is simply the right call. Pick LiteLLM over Everstack when any of these is true.

  • You need a provider LiteLLM supports and Everstack does not. Coverage breadth is LiteLLM's strongest card and it wins outright on this.
  • Routing is the whole problem. If you do not need agent sessions, sandboxes or evaluations, a gateway is the correct size of tool and adding a platform is over-buying.
  • You want the largest community. More worked examples, more integrations, more people who have hit your problem before.
  • You are a Python shop and want the SDK as well as the proxy. LiteLLM's library is a first-class way to use it; Everstack is a service you call.
  • The MIT core covers your needs. If you do not need virtual keys, SSO or spend-by-team, the enterprise directory never affects you and LiteLLM is free forever.
  • You want a project with years of production mileage rather than a young one. That is a legitimate risk position and Everstack cannot answer it yet.

Frequently asked questions

Common questions about choosing between Everstack and LiteLLM

Ready to get started?

See how Everstack compares to LiteLLM for your specific use case.

View pricingRead docs

Sources & References

LiteLLM licenceLiteLLM enterpriseBerriAI/litellm repositoryEverstack licence (Apache-2.0)

Last reviewed: August 31, 2026. This comparison is for informational purposes and reflects our understanding of competitor capabilities based on publicly available documentation.

← Back to all comparisons
Open-source AI infrastructure

Ship the AI stack
you can actually operate.

Start with one model call. Add agents, sandboxes, evaluations, memory, and traces without replacing the foundation underneath them.

Start with $5 creditSelf-host Everstack

One-time starter credit per account on Everstack Cloud. Expires 30 days after signup.