Ray Serve vs Valohai

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

The short answer

Valohai is the stronger AI pick in MLOps Platforms: it has a visibility score of 1.9 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 · Valohai 0pp over 0 weekly runs.

Valohai leads on 3 of 3 engines

ChatGPT

2.2%

AI Mode

Perplexity

3.5%

Ray ServeValohai

0 engine answers name both brands

0Ray Serve ranked higher

0Valohai ranked higher

Dimension	Ray Serve	Valohai
Pricing model	—	Per seat
Entry price	—	Contact sales
Free plan	—	No · 14-day trial
Deployment	Self-managed on a laptop, in a Docker container, on a managed Ray cluster, or on Kubernetes via KubeRay	Managed cloud, on-premises, private cloud or air-gapped environments, on the customer's own cloud infrastructure
Compliance	SOC 2 Type II, ISO/IEC 27001	SOC 2 Type II
Support	Ray Community Slack, Hands-on training and expert support from the Anyscale team that created Ray	Technical support from the Customer Engineering team, Valohai Training academy, Training and onboarding resources
Founded	—	2016
Headquarters	San Francisco, California	San Francisco, California, US
Employees	—	11–50
Funding	Series C	Seed · $2M raised
Best for	Python teams serving machine learning models, including LLMs, as online inference APIs that need independent scaling	AI product and ML teams that combine LLMs with specialized models and need to run the work on their own cloud or on-premises infrastructure