VectorAxis vs LiteLLM
This is not really a feature fight — it is a build-versus-buy decision. LiteLLM is free, open source, and yours to run; if you have the infrastructure appetite and want your traffic to never leave your own estate, it is an excellent and genuinely hard-to-beat choice. VectorAxis is a managed gateway: nothing to deploy, upgrade or page someone about at 3am, plus prepaid credits so you can skip provider accounts altogether. Pick LiteLLM if running it is a feature. Pick us if running it is a cost.
This comparison is written and maintained by VectorAxis. We are not affiliated with, or endorsed by, LiteLLM. Claims about LiteLLM were taken from their public documentation and pricing on — if we have something wrong, tell us and we will correct it.
What LiteLLM is
LiteLLM is an open-source unified interface to 100+ LLM providers. It ships as both a Python SDK and a self-hosted proxy server (the LiteLLM Gateway), deployable by CLI, Docker, Helm or cloud, with an admin UI, guardrails, and an Enterprise tier. You bring your own provider API keys and you run the infrastructure.
At a glance
| VectorAxis | LiteLLM | |
|---|---|---|
| Cost of the gateway itself | Free tier, then $40/month Pro. Managed — no infrastructure to pay for or run. | Free and open source. You pay for the servers, database and engineering time to run and maintain it. |
| Deployment | None. Change your base URL and go. | Self-hosted: CLI, Docker, Helm, or your cloud. You own uptime, scaling and upgrades. |
| Data path | Requests transit VectorAxis (managed). | Requests stay entirely inside your own infrastructure. For some teams this alone decides it. |
| Provider coverage | 56 providers routable through one OpenAI-compatible endpoint. | 100+ LLMs via a unified OpenAI-format interface. |
| Provider credentials | BYOK, or platform keys: buy prepaid credits and use ours for OpenAI, Anthropic, xAI and DeepSeek at a 5% service fee. | BYOK only — you export provider API keys into your deployment. |
| Guardrails | 31 built-in validators (PII, prompt injection, jailbreak, secrets, toxicity, topic restriction, schema/format, quality), deterministic and LLM-judge, on input and output. | Guardrails and policies are supported; several integrate third-party providers, and some capabilities sit in the Enterprise tier. |
| Caching | Exact-match and semantic caching (pgvector cosine similarity) with per-request TTL. | Caching supported, including semantic caching, typically backed by a Redis/vector store you run. |
| Observability | Hosted request logs, analytics and exports, retained per plan (3 days free, 30 days Pro). | Admin UI plus integrations into your own observability stack, which you host and retain. |
| Multimodal | Audio, images, files, batches and the Responses API through the same gateway and key. | Broad endpoint coverage including audio and images through the unified interface. |
| Who maintains it | We do. | You do — plus a large, very active open-source community. |
When LiteLLM is the better choice
There are real cases where we are not the right answer. If any of these describe you, use LiteLLM:
- Your data cannot leave your infrastructure. LiteLLM runs entirely inside your estate. No managed gateway, ours included, can offer that. If this is your constraint, the comparison is over and LiteLLM wins.
- You want zero vendor cost and have the engineering to run it. LiteLLM is free and open source. If a platform team is happy to own the deployment, the database, the upgrades and the on-call, that is a completely rational trade and it will be cheaper than us at scale.
- You want to read and modify the source. You can fork it, patch it, and audit exactly what happens to a request. We are closed source.
- You need a provider we do not route to. Their catalogue is larger. If your model is on their list and not among our 56, that decides it.
When VectorAxis is the better choice
- You do not want to operate a gateway. The real cost of LiteLLM is not the licence, it is the deployment, the Redis, the vector store, the upgrades and the pager. If that team does not exist, a managed gateway is cheaper than it looks.
- You want to start without provider accounts. Platform keys mean you top up credits and call OpenAI, Anthropic, xAI or DeepSeek immediately, at a 5% fee over provider rates — no OpenAI billing account, no Anthropic contract, one invoice. LiteLLM requires you to bring your own keys, which means signing up with every provider first.
- You want guardrails and observability without assembling them. 31 validators, request logs and analytics are part of the product rather than a stack you compose and host.
- You are not a Python shop. LiteLLM’s centre of gravity is Python. Our gateway is a network endpoint — any language, any OpenAI-compatible SDK, no dependency to add.
Common questions
Is LiteLLM really free?
The open-source project is free to use and self-host, and there is a paid Enterprise tier for additional features and support. What is not free is running it: servers, a database, a cache/vector store for semantic caching, upgrades, and someone on call. That total cost is the honest thing to compare against a VectorAxis plan, not zero.
Can I migrate from LiteLLM to VectorAxis without rewriting my code?
In most cases yes. Both speak an OpenAI-compatible API, so you change the base URL and the key. Your model strings, messages, streaming and tool-calling code stay the same. Configuration — routing rules, guardrails, prompt templates — has to be recreated; there is no automated importer.
Does VectorAxis keep my prompts?
Requests transit our managed gateway and are logged for the observability features you are paying for, with retention set by your plan (3 days on Free, 30 days on Pro). If prompts must never leave your own infrastructure, a self-hosted LiteLLM deployment is the correct answer, not us.
Do I still need OpenAI and Anthropic accounts with VectorAxis?
Not necessarily. That is the main practical difference from LiteLLM. With platform keys you buy prepaid credits from VectorAxis and we supply the provider credentials for OpenAI, Anthropic, xAI and DeepSeek, charging a 5% service fee on top of provider rates. You can also bring your own keys, in which case you pay providers directly and we add no per-token fee.