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Google Cloud Agent Evaluation

#20 of 28 in AI Agent Evaluation Tools

Google Cloud Agent Evaluation: A broad evaluation service for testing agent responses, traces, tools, and simulated scenarios. Ranked #20 of 28 in AI Agent Evaluation Tools by our editors (7.2/10); pricing: Paid; best for organizations wanting broad simulated agent evaluation.

7.2/10Editor score
Google Cloud Agent Evaluation7.2 Visit Google Cloud

At a glance

  • Editor score
    7.2 / 10
  • Pricing
    Paid
  • Best for
    Organizations wanting broad simulated agent evaluation
  • Tool-call checks
    Yes
  • Founded
    1998 · Mountain View, California, United States
  • Facts checked
    21 Sep 2026
Google Cloud Agent Evaluation screenshot
  • Where it wins

    • Covers final responses, tool-call trajectories, traces, and safety evaluation.
    • Combines exact match, BLEU, ROUGE, and rubric-based model metrics.
    • Supports offline, online, and simulated runs with case-level reports.
  • Where it doesn't

    • The agent-evaluation feature is labeled Preview.
    • It is a paid service requiring budget review before broad adoption.
    • Its scope may exceed the needs of teams seeking one narrow evaluation check.

Our verdict on Google Cloud Agent Evaluation

Google Cloud Agent Evaluation is a service for measuring AI-agent performance and quality across final answers and execution paths. It is aimed at developers and technical teams building or operating enterprise agents, including teams evaluating locally developed or deployed systems. The service supports web and API access and can work with production traces or generated scenarios.

Its standout strength is breadth. Teams can evaluate final responses, sequences of tool calls, recorded agent traces, safety behavior, and regression runs through hybrid methods. Computation-based metrics include exact match, BLEU, and ROUGE, while model-based metrics support customizable criteria and rubrics. Synthetic scenario generation, user simulation, and mocked tool behavior—including errors—make it suitable for examining how an agent behaves beyond a single response. Offline, online, and simulated evaluations provide different ways to inspect performance, with reports that include both aggregate and case-level results.

That range also defines the product’s trade-off. Organizations looking for a focused response checker may find its trajectory, trace, simulation, and tool-use capabilities broader than necessary. The agent-evaluation feature is labeled Preview, which matters for teams setting adoption expectations around a developing service. It is also paid, so broader use should fit an organization’s evaluation budget. Choose it when you need one service to examine responses, agent paths, tool interactions, traces, and simulated environments. Consider a narrower alternative when the requirement is limited to a single evaluation method or a simple response-level check.

Your product? Our editors can test Google Cloud Agent Evaluation in depth and publish a review, labelled as paid · from $149/mo →

Google Cloud Agent Evaluation pricing

Plans Paid No free plan — trial or paid only. Prices checked 21 Sep 2026.
See plans on docs.cloud.google.com

Google Cloud Agent Evaluation fact sheet

Free planNot verified
Paid fromNot verified
Evaluation methodsHybrid
Tool-call checksYes
Trace ingestionYes
Safety evaluationsYes
Regression runsYes
SDK language supportBoth
Dataset limitNot verified
DeploymentCloud
PlatformsWeb
Compliance & securitySOC 2, ISO 27001, GDPR, HIPAA, PCI DSS
SupportDocs, Community, Live chat, Phone, Tickets
Built forMid-market, Enterprise (editorial estimate)
PricingPaid (source)
Websitedocs.cloud.google.com
Facts checked21 Sep 2026

Alternatives to Google Cloud Agent Evaluation

See all Google Cloud Agent Evaluation alternatives →

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Featured on iTechGuides

Featured on iTechGuides — Google Cloud Agent Evaluation 7.2/10

Google Cloud Agent Evaluation is listed in our AI Agent Evaluation Tools directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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