H2O.ai vs Perpetual ML

H2O.ai

Two products under one name: a genuinely free, mature open-source ML library that data scientists have used for a decade, and an enterprise platform that only makes sense if your models must stay inside your own data centre. Evaluate them separately. The open-source side costs nothing to try; the commercial side is an annual licence negotiated after a demo, and its agentic layer is young compared with the AutoML core.

Pros

• +H2O-3 is Apache 2.0, distributed, and callable from R, Python, Scala, Java and a notebook UI
• +Commercial platform deploys on-premises, air-gapped, private cloud or managed cloud
• +One annual licence on compute and memory instead of per-token metering
• +Driverless AI AutoML, h2oGPTe and Document AI share one vendor and support contract

Cons

• −No public pricing or trial for the enterprise products; everything starts with a demo
• −The marketing now leads with a Super Agent orchestration story that is harder to evaluate than the AutoML core
• −Open-source H2O-3 and the paid platform are separate codebases, so free experiments do not simply upgrade
• −Self-hosting the full platform means owning GPUs, upgrades and integration work

Perpetual ML

Perpetual ML targets teams already living in Snowflake who want continual model retraining and monitoring without exporting data to a separate MLOps platform. The usage-based pricing is unusually transparent for this category, published down to the per-vCPU-second rate, but there's no public information about who runs the company or how long it has operated.

Pros

• +Usage-based pricing is published in detail (per-vCPU-second, per-GB-hour, per-task) rather than hidden behind a sales call
• +Continual learning avoids full retraining from scratch on every cycle
• +Covers the full lifecycle: training, registry, monitoring, and deployment in one product

Cons

• −No company name, founding date, or team information published anywhere on the site
• −Only Snowflake is supported today; Databricks is listed as upcoming, not available

Is H2O.ai cheaper than Perpetual ML?

Perpetual ML starts at $9.90/request. H2O.ai has a free tier; what its paid plans cost is not confirmed by us yet.

Does H2O.ai or Perpetual ML have a free tier?

Both: H2O.ai has a free tier, and Perpetual ML has a free tier.

Which has a public API, H2O.ai or Perpetual ML?

H2O.ai ships a public API, as of our last verification. A public API for Perpetual ML is not confirmed by us — check its developer docs before you plan an integration.