ModalCloud infrastructure for teams that develop, train, and serve AI applications at scale.
vs
Ray ServeScalable model serving library for building online inference APIs
Comparison · MLOps Platforms · weekly run Nov 2
Modal vs Ray Serve
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Modal is the stronger AI pick in MLOps Platforms: it has a visibility score of 1.3 versus 0 for Ray Serve.
Choose Modal if…
- You want the brand AI engines rank higher (1.3 vs 0)
- You need HIPAA coverage
- Strong for scaling cutting-edge generative AI and multi-modal models
Choose Ray Serve if…
- You need ISO/IEC 27001 coverage
AI visibility side by side
Latest weekly run · Nov 2
| Metric | Modal | Ray Serve |
|---|---|---|
| Visibility score | 1.3% | 0% |
| Change vs last week | New | New |
| Rank in MLOps Platforms | #36 | #61 |
| Share of voice | 0.5% | 0% |
| Mentions this run | 3 | 0 |
| Positive in AI answers | — | — |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Modal 0pp · Ray Serve 0pp over 0 weekly runs.
Engine by engine
Modal leads on 1 of 3 engines
ChatGPT
AI Mode
Perplexity
ModalRay Serve
Head to head in AI answers
0 engine answers name both brands
0Modal ranked higher
0Ray Serve ranked higher
Features, pricing & fit
| Dimension | Modal | Ray Serve |
|---|---|---|
| Pricing model | Usage-based | — |
| Entry price | Free; paid from $250 / mo | — |
| Free plan | Yes | — |
| Deployment | Serverless cloud capacity pooled from more than 20 cloud providers, with regions across the US, Europe, Asia Pacific and other areas. | Self-managed on a laptop, in a Docker container, on a managed Ray cluster, or on Kubernetes via KubeRay |
| Compliance | SOC 2 Type II, HIPAA | SOC 2 Type II, ISO/IEC 27001 |
| Support | Modal Community Slack on Starter and Team plans, Private Slack support and embedded ML engineering services on Enterprise | Ray Community Slack, Hands-on training and expert support from the Anyscale team that created Ray |
| Founded | 2021 | — |
| Headquarters | New York City, NY, United States | San Francisco, California |
| Employees | 201–500 | — |
| Funding | Series D · $1200M raised | Series C |
| Best for | Startups, independent developers and larger teams that run GPU inference, fine-tuning or agent sandboxes and want to pay only for compute used. | Python teams serving machine learning models, including LLMs, as online inference APIs that need independent scaling |
Plans side by side
Ray Serve
Pricing not available.
Pros and cons
Themes from the AI answers that mention each brand
Modal
- Strong for scaling cutting-edge generative AI and multi-modal models
Ray Serve
Profile in progress.
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Modal vs Ray Serve”, https://slateindex.ai/compare/modal-vs-ray-serve, data of Nov 2, 2026. Licence: CC BY 4.0.