Ray Serve vs ZenML

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

The short answer

ZenML is the stronger AI pick in MLOps Platforms: it has a visibility score of 6 versus 0 for Ray Serve.

Latest weekly run · Nov 2

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

Weekly runs over the last 60 days

Ray Serve 0pp · ZenML 0pp over 0 weekly runs.

ZenML leads on 3 of 3 engines

ChatGPT

11.7%

AI Mode

6.3%

Perplexity

Ray ServeZenML

0 engine answers name both brands

0Ray Serve ranked higher

0ZenML ranked higher

Dimension	Ray Serve	ZenML
Pricing model	—	Flat tiers
Entry price	—	Free; paid from $39 / mo
Free plan	—	Yes
Deployment	Self-managed on a laptop, in a Docker container, on a managed Ray cluster, or on Kubernetes via KubeRay	Self-hosted open source, or ZenML's cloud. Enterprise runs on-prem or air-gapped in the customer's cloud, with data and compute staying in the customer's VPC.
Integrations	—	66+
Compliance	SOC 2 Type II, ISO/IEC 27001	SOC 2 Type II, ISO 27001
Support	Ray Community Slack, Hands-on training and expert support from the Anyscale team that created Ray	Community Slack, Email, Dedicated support with SLA on Enterprise, Workshops and architecture reviews on Enterprise
Founded	—	2021
Headquarters	San Francisco, California	Munich, Germany
Employees	—	11–50
Funding	Series C	Seed extension · $6M raised
Best for	Python teams serving machine learning models, including LLMs, as online inference APIs that need independent scaling	Data science and ML engineering teams that want pipelines and AI agents run on their own infrastructure, and agent teams that want to find the evals they are missing.