PrefectWorkflow orchestration for data, ML, and agents
vs
Ray ServeScalable model serving library for building online inference APIs
Comparison · MLOps Platforms · weekly run Nov 2
Prefect vs Ray Serve
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Prefect is the stronger AI pick in MLOps Platforms: it has a visibility score of 0.7 versus 0 for Ray Serve.
Choose Prefect if…
- You want the brand AI engines rank higher (0.7 vs 0)
- You need GDPR compliant coverage
Choose Ray Serve if…
- You need ISO/IEC 27001 coverage
AI visibility side by side
Latest weekly run · Nov 2
| Metric | Prefect | Ray Serve |
|---|---|---|
| Visibility score | 0.7% | 0% |
| Change vs last week | New | New |
| Rank in MLOps Platforms | #42 | #61 |
| Share of voice | 0.3% | 0% |
| Mentions this run | 2 | 0 |
| Positive in AI answers | 0% | — |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Prefect 0pp · Ray Serve 0pp over 0 weekly runs.
Engine by engine
Prefect leads on 2 of 3 engines
ChatGPT
AI Mode
Perplexity
PrefectRay Serve
Head to head in AI answers
0 engine answers name both brands
0Prefect ranked higher
0Ray Serve ranked higher
Features, pricing & fit
| Dimension | Prefect | Ray Serve |
|---|---|---|
| Pricing model | Per seat | — |
| Entry price | Free; paid from $100 per seat / mo | — |
| Free plan | Yes | — |
| Deployment | Prefect Cloud fully managed with Prefect Serverless compute, or hybrid with lightweight workers inside the customer's own VPC | Self-managed on a laptop, in a Docker container, on a managed Ray cluster, or on Kubernetes via KubeRay |
| Compliance | SOC 2 Type II, GDPR compliant | SOC 2 Type II, ISO/IEC 27001 |
| Support | Community forum, Email, Priority support with 30-minute response SLA on enterprise plans | Ray Community Slack, Hands-on training and expert support from the Anyscale team that created Ray |
| Founded | 2018 | — |
| Headquarters | Washington, DC | San Francisco, California |
| Employees | 51–200 | — |
| Funding | Series B · $47M raised | Series C |
| Best for | Python data, ML, and agent teams that want durable production workflows without hosting their own scheduler | 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.
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Prefect vs Ray Serve”, https://slateindex.ai/compare/prefect-vs-ray-serve, data of Nov 2, 2026. Licence: CC BY 4.0.