DagsHubEverything you need to manage multimodal AI data & models.
vs
Ray ServeScalable model serving library for building online inference APIs
Comparison · MLOps Platforms · weekly run Nov 2
DagsHub vs Ray Serve
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
DagsHub is the stronger AI pick in MLOps Platforms: it has a visibility score of 3.5 versus 0 for Ray Serve.
Choose DagsHub if…
- You want the brand AI engines rank higher (3.5 vs 0)
- Structured annual pricing with yearly billing options on team tiers
- Recommended as a starting option for MLOps lifecycle coverage
Choose Ray Serve if…
- You need SOC 2 Type II or ISO/IEC 27001 coverage
AI visibility side by side
Latest weekly run · Nov 2
| Metric | DagsHub | Ray Serve |
|---|---|---|
| Visibility score | 3.5% | 0% |
| Change vs last week | New | New |
| Rank in MLOps Platforms | #23 | #61 |
| Share of voice | 0.6% | 0% |
| Mentions this run | 4 | 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
DagsHub 0pp · Ray Serve 0pp over 0 weekly runs.
Engine by engine
DagsHub leads on 3 of 3 engines
ChatGPT
AI Mode
Perplexity
DagsHubRay Serve
Head to head in AI answers
0 engine answers name both brands
0DagsHub ranked higher
0Ray Serve ranked higher
Features, pricing & fit
| Dimension | DagsHub | Ray Serve |
|---|---|---|
| Pricing model | Per seat | — |
| Entry price | Free; paid from $119 per seat / mo | — |
| Free plan | Yes | — |
| Deployment | Cloud hosting, with on-premise, VPC, and air-gapped installation on the Enterprise plan. | Self-managed on a laptop, in a Docker container, on a managed Ray cluster, or on Kubernetes via KubeRay |
| Compliance | — | SOC 2 Type II, ISO/IEC 27001 |
| Support | Community chat and email, Priority support on the Team plan, Enterprise SLA and support | Ray Community Slack, Hands-on training and expert support from the Anyscale team that created Ray |
| Founded | 2019 | — |
| Headquarters | San Francisco, California, United States | San Francisco, California |
| Employees | 11–50 | — |
| Funding | Accelerator/incubator deal | Series C |
| Best for | Data science and AI teams that manage multimodal datasets, experiments, and models, from individuals building small applications to enterprises running high-scale workloads. | Python teams serving machine learning models, including LLMs, as online inference APIs that need independent scaling |
Plans side by side
DagsHub
Individual$0user/month
Team$119user/month (monthly); $99 billed yearly
EnterpriseCustomcustom quote
Ray Serve
Pricing not available.
Pros and cons
Themes from the AI answers that mention each brand
DagsHub
- Structured annual pricing with yearly billing options on team tiers
- Recommended as a starting option for MLOps lifecycle coverage
Ray Serve
Profile in progress.
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “DagsHub vs Ray Serve”, https://slateindex.ai/compare/dagshub-vs-ray-serve, data of Nov 2, 2026. Licence: CC BY 4.0.