AI assistants and search decision
LLMBase
Keep paying for LLMBase if you need the curated EU-hosted model catalog, dedicated GPU endpoints and compliance guarantees; a competent developer can build a smaller OpenAI-compatible proxy/chat (losing many managed models, agent integrations, and enterprise infrastructure).
Visit website↗$9/mo
$108/yr
Read off the official pricing page.
$100one-off76 h to build
$50/mo6 h/mo upkeep
On cash alone, building overtakes the subscription at 7 seats.
Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All LLMBase alternatives, with the arithmetic →
What a replacement has to do
- Accept chat request → route to selected model via proxy API → receive and stream model response → store minimal conversation history → return tokens to web client
What it still won’t have
- Access to LLMBase's 40+ curated model catalog and managed European model endpoints
- Built-in agent integrations and agent marketplace discovery
- ISO 27001 / EU-hosted certified infrastructure and DPA support
- Priority queues, dedicated GPU endpoints, and enterprise SLAs
What remains hard
- Compliance and regulation
GDPR Compliant EU data protection workflows, DPA support, and transparent handling for teams that need privacy-first AI.
- Infrastructure at scale
Dedicated Endpoints Isolated GPU endpoints
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 7 seats.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a minimal OpenAI-compatible inference proxy and EU-hosted chat app using Node.js (Express) for the API, React for the web UI, PostgreSQL for user and usage data, and Docker for deployment on a single EU VM. Core features in scope: POST /v1/chat/completions proxy with streaming support, two provider adapters (OpenAI + Anthropic) selectable per request, simple React chat UI with model selector and token stream, JWT auth, per-user usage tracking and quota enforcement, conversation history storage, TLS deployment, and basic billing webhook to record payments. Out of scope: training models, multi-region autoscaling, full enterprise SLA, advanced agent marketplace. Require: error handling for provider failures and timeouts, unit tests for API adapters and auth, and integration test ensuring end-to-end chat flow with at least one provider mock.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 5 cited sources+3
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Hard moats found in the evidence-6
- Evidence score61
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Cited sources · 5
Every page the run actually retrieved.
- official productLLMBase homepage
- official pricingLLMBase pricing
- official docsLLMBase docs
- open sourceonyx repository
- open sourceFastGPT repository
Integrity checks
What held up, and what did not.
