Kubeflow vs Langfuse
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Kubeflow is the stronger AI pick in MLOps Platforms: it has a visibility score of 20.1 versus 0.3 for Langfuse, and ranks ahead in 100% of the answers that name both.
Choose Kubeflow if…
- You want the brand AI engines rank higher (20.1 vs 0.3)
- free and open source
- strong choice for Kubernetes-native, cloud-native ML platforms
- portability and deep infrastructure control
Choose Langfuse if…
- AI answers describe it more positively (50% vs 17% positive)
- You need SOC 2 Type II or ISO 27001 or HIPAA-ready region or GDPR coverage
- Discounted cloud pricing for qualifying early-stage startups
- Well suited to evaluating and debugging LLM or agent behavior
AI visibility side by side
Latest weekly run · Nov 2
| Metric | Kubeflow | Langfuse |
|---|---|---|
| Visibility score | 20.1% | 0.3% |
| Change vs last week | New | New |
| Rank in MLOps Platforms | #9 | #51 |
| Share of voice | 5.8% | 0.2% |
| Mentions this run | 39 | 1 |
| Positive in AI answers | 17% | 50% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Kubeflow 0pp · Langfuse 0pp over 0 weekly runs.
Engine by engine
Kubeflow leads on 3 of 3 engines
Head to head in AI answers
1 engine answers name both brands
| Prompt | Engine | Kubeflow | Langfuse |
|---|---|---|---|
| Top MLOps platform options for B2B SaaS companies | AI Mode | #7 | #10 |
Features, pricing & fit
| Dimension | Kubeflow | Langfuse |
|---|---|---|
| Pricing model | — | Usage-based |
| Entry price | — | Free; paid from $29 / mo |
| Free plan | — | Yes |
| Deployment | Runs as a collection of microservices on any Kubernetes cluster, including on-premises, hybrid, and AWS, Azure, or GCP. | Langfuse Cloud in US, EU, Japan and HIPAA regions, or self-hosted under the MIT license |
| Integrations | — | 100+ |
| Compliance | — | SOC 2 Type II, ISO 27001, HIPAA-ready region, GDPR |
| Support | Weekly community calls, Mailing list, Slack workspace | 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 |
| Founded | 2017 | — |
| Headquarters | Sunnyvale, CA, United States | — |
| Employees | 51–200 | — |
| Funding | — | Seed · $4M raised |
| Best for | — | Engineering teams building LLM applications and AI agents that want open-source, self-hostable tracing and evaluation |
Plans side by side
Kubeflow
Pricing not available.
Pros and cons
Themes from the AI answers that mention each brand
Kubeflow
- free and open source
- strong choice for Kubernetes-native, cloud-native ML platforms
- portability and deep infrastructure control
- modular, open-source infrastructure
- operationally complex, especially for small teams
- requires Kubernetes expertise and significant infrastructure ownership
- Kubernetes operations add infrastructure costs
Langfuse
- Discounted cloud pricing for qualifying early-stage startups
- Well suited to evaluating and debugging LLM or agent behavior
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Kubeflow vs Langfuse”, https://slateindex.ai/compare/kubeflow-vs-langfuse, data of Nov 2, 2026. Licence: CC BY 4.0.