Usage-based pay-as-you-go pricing with hourly compute charges; committed contracts available for volume discounts. Hosted option with Anyscale-managed infrastructure or Bring Your Own Cloud deployment available.
Free for one developer with up to 25 source-built services, 50,000 tool calls a month, then $0.20 per thousand. Team plan is $25 per developer per month with 100,000 tool calls per developer a month, pooled, then $0.20 per thousand. Enterprise from $1,500 per month.
Key features
Multimodal data curation at scale
Distributed model training with elastic scaling
Batch embedding generation at scale
Multi-cloud deployment and orchestration
Cluster-backed development environments
Workload-specific observability and debugging
Production-grade managed Ray clusters
Access control and governance
GPU budget controls and cost attribution
Post-training with SkyRL and veRL support
Source-built servers with TypeScript or Python projects
Remote MCP, OpenAPI, npm package, and container image support
Per-tool and per-argument access control policies
Tool definition review and approval workflow
Content scanning with literal and regex detectors
Activity tracking and audit trails
OIDC and SAML 2.0 single sign-on
SCIM 2.0 provisioning
Workspace-specific data encryption
Custom domain publishing with DNS and Cloudflare certification
What makes it different
Built by creators of Ray, the world's most widely adopted AI compute engine
Multi-cloud deployment without code changes
Feels local but runs distributed
Unified GPU pooling across clouds and regions
One endpoint replaces every client config, eliminating need for each client to store every server and secret
Coding agent builds the server automatically with no adapter needed
Credentials held once by Rayrun instead of distributed across clients
Built-in security review with published controls and audit trails for compliance teams
Support for multiple service types without writing adapters
Rayrun