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Introducing Span-02

Lunary vs MLflow (2026)

Updated March 27, 2026

vs

Overview

Rating
10.0 / 10
Rating
10.0 / 10
Best For
—
Best For
ML engineers and AI teams, especially those in the Databricks ecosystem
Product Summary

Lunary is an open-source LLM observability platform for monitoring AI applications in production. It provides request tracing, cost tracking, user analytics, and prompt management with a clean dashboard. Lunary can be self-hosted for data privacy and offers a managed cloud option.

Product Summary

MLflow is an open-source AI engineering platform for agents, LLMs, and ML models, with tracing, evals, prompt management, and an AI gateway.

Starting Price
$0Per month
Starting Price
Free
Free Trial
Yes
Free Trial
No
Free Version
Yes
Free Version
Yes
Website
Website

Key features

Core capabilities each platform advertises.

LunaryLunary
Data not available
MLflowMLflow
  • OpenTelemetry-based tracing for LLMs and agents
  • 50+ built-in eval metrics and LLM judges
  • Prompt versioning and automatic prompt optimization
  • AI Gateway with routing, rate limiting, and fallbacks
  • Agent server for deploying agents on FastAPI

Strengths and tradeoffs

What each tool does well, and the limitations to keep in mind.

LunaryLunary

Pros

  • Production-ready platform
  • Good performance
  • Active development
  • Strong features

Cons

  • Enterprise pricing varies
  • Setup complexity
  • Learning curve required
MLflowMLflow

Pros

  • Apache 2.0 license with Linux Foundation governance
  • Tracing, evals, prompts, and a gateway in one open-source project
  • Covers classic ML and GenAI in the same platform
  • Managed options on Databricks, SageMaker AI, and Azure ML
  • Auth and role-based access built into the open-source server

Cons

  • Self-hosting means running the tracking server, database, and artifact store yourself
  • Auth and role-based access are opt-in and need configuring on self-hosted servers
  • Managed versions bill through a cloud platform's compute rather than a standalone plan
  • The broader ML scope can mean more to learn for teams that only need LLM tooling

Lunary or MLflow — which should you choose?

Choose Lunary if you want

Data not available

Choose MLflow if you want

  • Tracing and evaluating LLM apps and agents
  • Versioning and optimizing prompts
  • Routing LLM traffic through a self-hosted gateway
  • Tracking classic ML experiments alongside GenAI work
  • Running AI tooling inside Databricks

Compare Lunary and MLflow on your own traffic

10KFree traces/mo
1,000+Models
5 minSetup

Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 1,000+ models through one gateway.

Try Respan free

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