MLflow vs W&B Weave
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.
W&B Weave
Weights & Biases' LLM tracing and evaluation product, now owned by CoreWeave after a reported $1.7B acquisition. Billed on GB of trace data ingested rather than spans or requests, which is a genuinely different cost model to everything else in the category.
| MLflow | W&B Weave | |
|---|---|---|
| Category | Observability & Tracing | Observability & Tracing |
| Our rating | 4/5 | 4/5 |
| Starting price | $0 (open source) | Per-seat plus usage |
| Billing meter | No usage metering | gb-ingested |
| Free plan | Yes | Yes |
| Free self-hosting | Yes, free | No or paid tier only |
| 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 already running Weights & Biases for model training and experiment tracking, who want LLM traces and evals in the same platform as their fine-tuning runs and are comfortable with usage-based ingestion billing. |
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 W&B Weave
W&B Weave is the strongest option in the category for one specific team - the one already on Weights & Biases. The lineage story is real and unmatched - a model fine-tuned in Sweeps and the eval run testing it appear in the same interface, which no AI-native competitor can offer because none of them do training. The instrumentation API is excellent, the custom scorers are plain Python, and the integration coverage is among the broadest available. Two things temper it. The billing metric is GB of trace data ingested, which is genuinely harder to forecast than per-span or per-seat pricing because it scales with prompt and context size, not just traffic. And CoreWeave now owns it following a reported $1.7B acquisition, which has come with interoperability pledges but leaves an open question about long-term direction. If you are not already a W&B customer, the bundled per-seat maths works against you and there are cheaper focused tools.
Full W&B Weave review →Frequently Asked Questions
What is the main difference between MLflow and W&B Weave?
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. W&B Weave: Teams already running Weights & Biases for model training and experiment tracking, who want LLM traces and evals in the same platform as their fine-tuning runs and are comfortable with usage-based ingestion billing. 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 W&B Weave?
It depends entirely on your workload shape, because they meter differently - MLflow bills on no usage metering and W&B Weave bills on gb-ingested. Published starting prices are $0 (open source) and Per-seat plus usage 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 W&B Weave?
MLflow: Yes, free. W&B Weave: No or paid tier only. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.