Galileo vs OpenLIT
Both are observability & tracing tools. Here is how they actually differ on price, billing model and deployment.
Galileo
The best-funded evaluation-and-observability platform in this space, built around proprietary Luna eval models. Not to be confused with the Google-acquired text-to-UI tool of the same name. Real pricing is sales-led above $100/mo.
OpenLIT
Apache-2.0 OpenTelemetry-native platform covering LLM tracing, evals, prompts, guardrails and a Vault - plus the one thing nearly every competitor ignores entirely, GPU monitoring for self-hosted inference.
| Galileo | OpenLIT | |
|---|---|---|
| Category | Observability & Tracing | Observability & Tracing |
| Our rating | 4/5 | 4/5 |
| Starting price | $100/mo | $0 (Apache 2.0) |
| Billing meter | span | No usage metering |
| Free plan | Yes | Yes |
| Free self-hosting | No or paid tier only | Yes, free |
| Best for | Enterprise GenAI teams that have been burned by production hallucinations and want research-grade eval metrics plus guardrails, and can run a sales process | Teams running self-hosted inference on their own GPUs, where correlating GPU health with model performance matters. Also a strong free choice for anyone wanting broad AI engineering tooling in one Apache-2.0 package. |
Our verdict on Galileo
Galileo is the best-funded and arguably most research-forward platform here, and the Luna eval models are a real bet on making evaluation cheap enough to run continuously. Two caveats. First, make sure you're evaluating this Galileo and not the design tool that shares the name - the pricing and reviews get conflated constantly. Second, above the $100 Pro tier everything is contact-sales, and self-host is Enterprise-only, so this is a platform you buy through a rep, not a card.
Full Galileo review →Our verdict on OpenLIT
OpenLIT is the only tool in this category that takes the GPU layer seriously, and if you run your own inference that alone may decide it. Its OpenTelemetry GPU collector exports utilisation, memory, temperature and power as standard OTel signals, so you can correlate a latency regression with thermal throttling or a KV cache leak in the same dashboard - a class of problem that is completely invisible to Langfuse, LangSmith or Braintrust, because they assume you call an API. Beyond that it is unusually broad for a free tool - Apache 2.0 across the core, covering observability, evals, guardrails, prompt management, a Vault and a Playground. The trade-off is breadth over depth, since each module is lighter than a dedicated competitor, and the community is small at roughly 2,500 stars. Two things we could not resolve - an enterprise eBPF controller is referenced without clear licensing terms, and the project has recently described itself as a Harness Engineering platform without public explanation of what that means.
Full OpenLIT review →Frequently Asked Questions
What is the main difference between Galileo and OpenLIT?
Galileo: Enterprise GenAI teams that have been burned by production hallucinations and want research-grade eval metrics plus guardrails, and can run a sales process OpenLIT: Teams running self-hosted inference on their own GPUs, where correlating GPU health with model performance matters. Also a strong free choice for anyone wanting broad AI engineering tooling in one Apache-2.0 package. Both sit in Observability & Tracing, so the decision usually comes down to billing model and deployment rather than raw capability.
Which is cheaper, Galileo or OpenLIT?
It depends entirely on your workload shape, because they meter differently - Galileo bills on span and OpenLIT bills on no usage metering. Published starting prices are $100/mo and $0 (Apache 2.0) respectively, but those numbers are not comparable until you apply them to the same traffic. Use our cost calculator to model both against your own request volume and span count.
Can I self-host Galileo or OpenLIT?
Galileo: No or paid tier only. OpenLIT: Yes, free. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.