LiteLLM Alternative
Looking for a LiteLLM alternative?
LiteLLM is a genuinely good open-source gateway, and if routing is your problem it is hard to beat. The catch is everything around it: a gateway to deploy, a database to keep, and spend data built for engineers. AI SpendOps is the managed alternative, adding finance-grade cost accounting, budgets, governance and reporting on top of gateway routing, with no infrastructure to run.
Where LiteLLM fits, and where it stops
LiteLLM solved the routing problem: one OpenAI-compatible endpoint in front of 100+ providers, with fallbacks, load balancing and virtual keys. It also tracks spend per key, user and team in your own database, and supports budgets. That is real cost tracking, and we are not going to pretend otherwise.
Where teams start looking for an alternative is what happens after routing. Someone has to run the gateway, the Postgres behind it and Redis once you scale past one instance. The spend view answers “which key spent what” rather than “what did this feature cost us per customer last month”. And the governance controls finance and security ask for, tag-based spend reports, RBAC, SSO and audit logs, sit behind an Enterprise licence. If that is the gap you are feeling, this page is for you.
AI SpendOps vs LiteLLM
| AI SpendOps | LiteLLM | |
|---|---|---|
| Licence & hosting | Managed service on the edge | Open source, you self-host |
| Infrastructure you run | None | Gateway, Postgres, Redis at scale |
| Drop-in integration (base URL change) | ||
| Providers in one gateway | 16+ | 100+ |
| Routing (fallbacks, load balancing, caching) | Pass-through, no routing logic | Extensive |
| Per-request token & cost capture | ||
| Spend tracking & budgets | Yes, backed by your database | |
| Attribution by team, feature, env & customer | Custom dimensions, every plan | Tag-based spend reports (Enterprise) |
| SSO, RBAC & audit logs | Included | Enterprise licence |
| Reporting audience | Finance and engineering, same numbers | Engineer-facing admin UI and APIs |
| Cache, reasoning & modality tokens split out | Partial, varies by provider | |
| Prompt & response storage | Never stored, metadata only | Configurable, you decide |
| Pricing | From £29/mo, first 3 months free | Free OSS plus your infra, Enterprise quoted |
Comparison based on publicly available LiteLLM documentation as of August 2026, including its open source versus Enterprise feature list. LiteLLM features move quickly, so check their docs for the current position. LiteLLM is a trademark of its respective owners; this page is provided for comparison purposes only.
An honest answer
When to choose which
These tools overlap, but they are not aimed at the same job. Here is where each one wins, including the cases where LiteLLM is the better answer.
Choose LiteLLM if
- You want open source you can read, fork and run inside your own network
- You need the long tail of providers, or one we do not support yet
- Routing is the point: fallbacks, load balancing, retries and semantic caching
- You have a platform team happy to own a gateway, a database and its upgrades
- Budgets and spend data are for engineers, and engineers alone
Choose AI SpendOps if
- Finance needs AI spend it can report, attribute and defend, not a spend table to query
- Nobody wants to run and page for another gateway, database and cache
- You need cost per feature, per customer and per environment across providers
- Prompts and responses must never be stored anywhere, as a hard requirement
- SSO, RBAC and audit logs are needed now, not after an enterprise negotiation
Not mutually exclusive: if LiteLLM is doing routing you depend on, keep it and point its provider base URLs at AI SpendOps, so every call still lands in one finance-grade ledger. Talk to us about that setup.
Migrating from LiteLLM
A base-URL change, then decommission the gateway
If you run the LiteLLM proxy, your services already point at a base URL, so moving is a config change rather than a rewrite. If you call the LiteLLM Python SDK inside your application, you go back to the official provider SDK and point it at our gateway, which is a few lines per service.
- Swap your LiteLLM base URL for proxy.aispendops.com
- Add your X-ASO-API-Key header, and keep your own provider keys
- Move your virtual keys to AI SpendOps keys, one per team, service or environment
- Re-tag calls with custom dimensions for team, feature, environment and customer
- Verify spend for a day in parallel, then retire the gateway, Postgres and Redis
Historic spend stays in your LiteLLM database, so keep a snapshot if you need the back history. New spend starts accruing in AI SpendOps from the first request.
Nothing to self-host
The gateway you do not have to run
Free software still has a bill: the instances, the database, the on-call rota and the upgrades. AI SpendOps runs on Cloudflare’s global edge with usage capture moved entirely off the response path, so it scales with your traffic and none of it is yours to operate.
No gateway containers, no Postgres, no Redis, no upgrade path to own. You change a base URL and the platform is live.
Every request is served from the location nearest your users, without you provisioning a single region.
Usage, cost and token capture run asynchronously after the response is sent, so the proxy stays off your critical path.
What AI SpendOps adds
The same drop-in, BYO-key proxy model you already know from LiteLLM, built for financial accountability and governance instead of engineering plumbing.
Finance-grade accounting, not a spend table
LiteLLM records what each key spent. AI SpendOps maps every token to a team, feature, environment and customer, reconciles it against provider pricing, and presents it in reports finance can actually file. Engineering and finance read the same numbers.
Nothing to run, nothing to keep running
Self-hosting LiteLLM means a gateway to deploy, a database to back up, Redis for multi-instance rate limiting, and someone on call for all of it. AI SpendOps is a managed edge service, so the total cost of ownership is the subscription and nothing else.
Governance without an enterprise licence
SSO, role-based access control, audit logs and tag-based spend reports sit behind LiteLLM's Enterprise tier. On AI SpendOps they are part of the product, alongside model and provider allow-lists enforced at the edge before a request reaches your provider.
Prompts are never stored, by design
LiteLLM can log request and response content, and how much it keeps is your configuration to get right. AI SpendOps extracts usage metadata only. There is no setting to misconfigure and no prompt corpus to defend in a security review.
Frequently asked questions
Is AI SpendOps a replacement for LiteLLM?
For cost tracking, attribution, budgets and governance, yes. Both are OpenAI-compatible base-URL proxies, so pointing your SDK at AI SpendOps instead gives you the same drop-in model with finance-grade reporting and no infrastructure. If you rely on LiteLLM specifically for routing logic such as fallbacks, load balancing or semantic caching, AI SpendOps does not replace that, because it deliberately passes requests through rather than rewriting them.
Does LiteLLM already do cost tracking and budgets?
It does, and honestly so. The open-source proxy tracks spend per key, user, team and model in your own database, and supports per-key and per-team budgets. The differences are who the numbers are built for and what they cost to run. LiteLLM reporting is engineer-facing and requires you to operate a gateway plus a database, and features such as tag-based spend reports, RBAC, SSO and audit logs require an Enterprise licence.
Can I keep LiteLLM and use AI SpendOps as well?
Yes. LiteLLM talks to providers over configurable base URLs, so you can keep it for routing and point its provider base URLs at the AI SpendOps gateway. Requests still route the way you have configured them, and every call lands in one finance-grade ledger with full attribution. Get in touch and we will help you wire it up.
How hard is it to migrate from LiteLLM to AI SpendOps?
If you already run the LiteLLM proxy, your applications are pointed at a base URL, so you swap that URL and add a single X-ASO-API-Key header. If you call the LiteLLM Python SDK directly, you move back to the official provider SDK and point it at our gateway, which is usually a few lines per service. You keep your own provider keys either way, and runnable examples for Python, TypeScript and .NET are in our open-source examples repo.
Do I keep my own provider API keys?
Yes. AI SpendOps is BYO-key: you keep your own OpenAI, Anthropic and other provider keys, you keep using the official SDKs, and you can turn the proxy off in a single config line. No lock-in, and no migration of credentials.
Is AI SpendOps open source?
No. AI SpendOps is a managed service rather than a self-hosted open-source project, which is the main trade-off against LiteLLM. Our integration examples for Python, TypeScript and .NET are open source under the MIT licence, and because you keep your own provider keys and standard SDKs, leaving is a base-URL change.
Keep the gateway, lose the gateway ops
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