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Langfuse vs MLflow

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors.

The short answer

Free plan
Both — Langfuse has a free plan, MLflow is free to use
Public API
Both have one
Higher Trust score
MLflow — 94 vs 80 for Langfuse
Best fit
Langfuse: Engineering teams running LLM apps or agents in production who need traces and cost tracking · MLflow: ML teams that need experiment tracking and a model registry without vendor lock-in
Platforms
Langfuse: Web · MLflow: Linux, macOS, Windows

From our own records as of each tool's last check. Anything we have not confirmed is left out rather than guessed. How we verify

LangfuseOpen-source LLM engineering platform for tracing agents, versioning prompts, running evals and tracking cost, hosted or self-hosted.MLflowOpen-source platform for tracking ML experiments, registering models and tracing, evaluating and deploying LLM agents.

Side by side

FactLangfuseMLflow
CategoryLLM Observability & EvaluationMLOps & Experiment Tracking
Pricing modelFreemiumFree
Starts at$29/mo—
Public APIYesYes
Trust score80 / 10094 / 100
PlatformsWeb, APILinux, macOS, Windows, API
CompanyLangfuse GmbHMLflow Project (LF Projects, LLC)
Launched20232018
Last verifiedOct 29, 2026Oct 2, 2026

What our research says

Langfuse

Langfuse is a strong default for teams that want tracing, prompt versioning and evaluations in one open-source tool, with the option to keep data on their own infrastructure. Teams that only want a hosted logging proxy with no SDK work, or that need guaranteed enterprise SSO without paying for add-ons, may find simpler or more bundled options.

Pros

  • MIT-licensed core that can be self-hosted without usage limits
  • Covers tracing, prompt management, evaluation and dashboards in one product
  • Generous free cloud tier and unlimited users from the $29 Core plan
  • OpenTelemetry support and SDKs for Python and JavaScript

Cons

  • Usage above the included 100k units is billed extra, so busy apps pay more than the headline price
  • Free tier keeps only 30 days of data and two users
  • Enterprise SSO and RBAC require the $300 Teams add-on on Pro or the Enterprise plan

MLflow

The default open-source choice for tracking experiments and registering models, now extended to cover tracing, evaluation and prompt management for LLM agents. It is free and runs anywhere, but it is infrastructure you operate rather than a polished SaaS. Teams that want a hosted experience should look at a managed offering or a commercial LLMOps vendor.

Pros

  • Apache 2.0, self-hostable, no usage fees
  • Covers classical ML, LLM tracing, evaluation, prompts and a gateway in one project
  • Integrates with 100+ frameworks and OpenTelemetry
  • Backed by a large community and the Linux Foundation project structure

Cons

  • You run and scale the tracking server yourself
  • Broad scope means a steeper learning curve than single-purpose tools
  • Newer LLM features are still evolving quickly

Which one fits

Choose Langfuse if you need

  • Engineering teams running LLM apps or agents in production who need traces and cost tracking
  • Organisations that must self-host observability data for compliance
  • Teams that want prompts, datasets and evals tied to the same traces

Choose MLflow if you need

  • ML teams that need experiment tracking and a model registry without vendor lock-in
  • Developers who want open-source tracing and evals for LLM apps and agents
  • Organizations already on Databricks or other clouds that offer managed MLflow

Langfuse vs MLflow: the questions people ask

Is Langfuse cheaper than MLflow?

MLflow is free to use; Langfuse starts at $29/mo.

Does Langfuse or MLflow have a free tier?

Both: Langfuse has a free tier, and MLflow is free to use.

Which has a public API, Langfuse or MLflow?

Both ship a public API, so either can be built on; the fact table above shows the platforms each one runs on.

More comparisons

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