OpenLIT vs Langtrace
Both are observability & tracing tools. Here is how they actually differ on price, billing model and deployment.
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.
Langtrace
An OpenTelemetry-native open-source tracing tool from Scale3 Labs. The cloud is still free because it has never been monetised - which is either a bargain or a runway risk depending on how you read a seed round raised around 2022. The AGPL-3.0 server license is the other thing to check before you commit.
| OpenLIT | Langtrace | |
|---|---|---|
| Category | Observability & Tracing | Observability & Tracing |
| Our rating | 4/5 | 3/5 |
| Starting price | $0 (Apache 2.0) | Free (not yet monetised) |
| Billing meter | No usage metering | No usage metering |
| Free plan | Yes | Yes |
| Free self-hosting | Yes, free | Yes, free |
| Best for | 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. | Teams that want OpenTelemetry-native tracing with strong vector database visibility, are comfortable with AGPL on the server, and can tolerate the possibility of a pricing model appearing later. |
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 →Our verdict on Langtrace
Langtrace is a well-built OpenTelemetry-native tracing tool with unusually good vector database instrumentation, and right now it costs nothing. Two things stop us rating it higher, and neither is about the product quality. The first is the license - the application is AGPL-3.0 while the SDKs are Apache 2.0, and that split matters. Instrumenting your app is safe; modifying the server and offering it as a service brings copyleft obligations most commercial teams will want legal review on. The second is commercial. The vendor states it is not currently charging for the cloud and will announce when it decides to monetise, and public funding data shows a roughly $5.3M seed raised around 2022. A free cloud with no revenue model and a four-year-old seed round is not a stable planning assumption. Use it, and self-host if it becomes load-bearing.
Full Langtrace review →Frequently Asked Questions
What is the main difference between OpenLIT and Langtrace?
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. Langtrace: Teams that want OpenTelemetry-native tracing with strong vector database visibility, are comfortable with AGPL on the server, and can tolerate the possibility of a pricing model appearing later. Both sit in Observability & Tracing, so the decision usually comes down to billing model and deployment rather than raw capability.
Which is cheaper, OpenLIT or Langtrace?
It depends entirely on your workload shape, because they meter differently - OpenLIT bills on no usage metering and Langtrace bills on no usage metering. Published starting prices are $0 (Apache 2.0) and Free (not yet monetised) 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 OpenLIT or Langtrace?
OpenLIT: Yes, free. Langtrace: Yes, free. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.