Langfuse vs MLflow

Which one do AI engines recommend, and how do they differ on price, fit and features?

The short answer

MLflow is the stronger AI pick in MLOps Platforms: it has a visibility score of 50.9 versus 0.3 for Langfuse, and ranks ahead in 100% of the answers that name both.

Choose Langfuse if…

AI answers describe it more positively (50% vs 44% positive)
You need a self-hosted or on-premises option
You need SOC 2 Type II or ISO 27001 or HIPAA-ready region or GDPR coverage
Discounted cloud pricing for qualifying early-stage startups

Choose MLflow if…

You want the brand AI engines rank higher (50.9 vs 0.3)
free open-source software with no license fee
widely adopted MLOps standard and baseline
experiment tracking and model registry

AI visibility side by side

Latest weekly run · Nov 2

Metric	Langfuse	MLflow
Visibility score	0.3%	50.9%
Change vs last week	New	New
Rank in MLOps Platforms	#51	#1
Share of voice	0.2%	9.7%
Mentions this run	1	65
Positive in AI answers	50%	44%

The stronger value in each row is marked with a ✓.

Visibility score trend

Weekly runs over the last 60 days

Langfuse 0pp · MLflow 0pp over 0 weekly runs.

Engine by engine

MLflow leads on 3 of 3 engines

ChatGPT

48.5%

AI Mode

0.9%

60.6%

Perplexity

43.7%

LangfuseMLflow

Head to head in AI answers

1 engine answers name both brands

0Langfuse ranked higher

1MLflow ranked higher

Prompt	Engine	Langfuse	MLflow
Top MLOps platform options for B2B SaaS companies	AI Mode	#10	#2

Features, pricing & fit

Dimension	Langfuse	MLflow
Pricing model	Usage-based	—
Entry price	Free; paid from $29 / mo	—
Free plan	Yes	—
Deployment	Langfuse Cloud in US, EU, Japan and HIPAA regions, or self-hosted under the MIT license	Self-hosted from the open source package, started with one command or Docker.
Integrations	100+	100+
Compliance	SOC 2 Type II, ISO 27001, HIPAA-ready region, GDPR	—
Support	Community support via GitHub, In-app support, Private Slack or MS Teams channel on Pro and Enterprise plans, Named lead support engineer on Enterprise plans	Documentation, Community Slack, Mailing list mlflow-users@googlegroups.com, GitHub
Founded	—	2018
Headquarters	—	San Francisco, CA, United States
Funding	Seed · $4M raised	—
Best for	Engineering teams building LLM applications and AI agents that want open-source, self-hostable tracing and evaluation	Teams of all sizes building LLM applications, agents and ML models who want open source tooling without vendor lock-in.