The industry standard for ML lifecycle management. The 2025 release of MLflow 3.0 drastically expanded its scope to include comprehensive GenAI agent evaluation
MLflow is the open-source spine of ML/LLM operations: experiment tracking, model registry, and, since 3.x, first-class GenAI features: LLM tracing, prompt registries, and evaluation runs. It's the vendor-neutral choice for teams standardizing AI lifecycle management.
Pricing: Open-source (Apache 2.0); managed offerings ship inside Databricks and cloud platforms.
LangSmith vs MLflow (2026): LangSmith delivers the slickest tracing-evals-datasets loop for LangChain/LangGraph teams. MLflow 3.x is the open, vendor-neutral standard spanning classic ML and GenAI in one lineage system: the default for platform-neutral organizations and Databricks shops. Framework alignment usually decides.
Yes: MLflow 3.x added tracing for LLM/agent calls, prompt versioning, and evaluation tracking, making it a credible open alternative to commercial LLM observability platforms.
LangSmith offers the slickest LangChain-native experience; MLflow offers open standards across the whole ML+GenAI estate. Platform-neutral organizations and Databricks shops lean MLflow.