MLflow vs Langtrace
Both are observability & tracing tools. Here is how they actually differ on price, billing model and deployment.
MLflow
The open-source ML platform that grew a serious GenAI half. MLflow 3 adds OpenTelemetry-compatible tracing, LLM judges and review apps - free and self-hostable, with Databricks selling the managed version. The best zero-cost option if you can run infrastructure.
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.
| MLflow | Langtrace | |
|---|---|---|
| Category | Observability & Tracing | Observability & Tracing |
| Our rating | 4/5 | 3/5 |
| Starting price | $0 (open source) | 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 that already run MLflow for classical ML, Databricks customers, and anyone who wants a genuinely free and complete self-hosted platform and has the operational capacity to run it. | 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 MLflow
MLflow is the strongest zero-cost option in the category, with the caveat that free software is not free to operate. MLflow 3 turned what was an experiment-tracking tool into a real GenAI platform - OpenTelemetry-compatible tracing from a single line of code, built-in and custom LLM judges, review apps that collect expert feedback and align automated judges against it, and evaluation datasets built directly from production traces. It is Apache 2.0 and the open-source build is complete rather than a gated teaser, which is more than can be said for several commercial competitors advertising self-hosting. Two honest caveats. The UI is functional rather than pleasant, and it shows its lineage as a tool built for ML engineers rather than application developers. And the genuinely best-governed experience - Unity Catalog trace storage in OTel Delta tables, no storage cap, SQL queryable - is available on Databricks, which is where the commercial gravity sits. If you already run MLflow or Databricks, this is close to automatic.
Full MLflow 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 MLflow and Langtrace?
MLflow: Teams that already run MLflow for classical ML, Databricks customers, and anyone who wants a genuinely free and complete self-hosted platform and has the operational capacity to run it. 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, MLflow or Langtrace?
It depends entirely on your workload shape, because they meter differently - MLflow bills on no usage metering and Langtrace bills on no usage metering. Published starting prices are $0 (open source) 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 MLflow or Langtrace?
MLflow: Yes, free. Langtrace: Yes, free. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.