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.
Not given
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
LLM trace logging with 40+ integrations
Automatic error detection and diagnostics
Ollie agent for code fix recommendations
Test Suites and 40+ LLM-as-a-judge evaluation metrics
Production dashboards and alerts for agents
Prompt playground and optimization
Agent Playground for local agent development
Cost intelligence for Claude Code and Codex tracking
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
Truly open-source platform with enterprise-grade infrastructure
Traces appear almost instantly even at high volumes
Flexible hosting options including self-hosted, cloud, and custom deployments
Easy integration with just a few lines of code
Opik automatically turns trace data and eval results into code fixes