Vertex AI Gen AI Evaluation Service vs Amazon Bedrock Evaluations
Both are agent evaluation tools. Here is how they actually differ on price, billing model and deployment.
Vertex AI Gen AI Evaluation Service
Google's evaluation service, whose defining feature is adaptive rubrics - a unique set of pass/fail criteria generated per prompt, working like unit tests. Now branded under the Gemini Enterprise Agent Platform.
Amazon Bedrock Evaluations
AWS-native model and agent evaluation, billed per evaluation job. The recurring criticism is fragmentation - CloudWatch, Prompt Flows and Evaluations look like one product on paper and behave like three in practice.
| Vertex AI Gen AI Evaluation Service | Amazon Bedrock Evaluations | |
|---|---|---|
| Category | Agent Evaluation | Agent Evaluation |
| Our rating | 4/5 | 3/5 |
| Starting price | Per token plus GCP compute | Per evaluation job |
| Billing meter | No usage metering | job |
| Free plan | No | No |
| Free self-hosting | No or paid tier only | No or paid tier only |
| Best for | Teams on Google Cloud running model migrations, prompt changes or fine-tuning comparisons, who want per-prompt evaluation criteria rather than a fixed metric set. | Teams already committed to Bedrock who want evaluation inside their existing AWS account and IAM boundary, and who value procurement simplicity over best-in-class agent tooling. |
Our verdict on Vertex AI Gen AI Evaluation Service
Vertex AI's evaluation service has the most interesting single idea among the cloud platforms - adaptive rubrics. Rather than applying the same metric set to every prompt, it generates a unique set of pass/fail rubrics for each one, and the framing Google uses is exactly right - rubrics act like unit tests. Comparing two models becomes evaluating their responses against the same generated tests and comparing pass rates, which is far easier to reason about than comparing averaged similarity scores, and far more informative about what specifically broke. It also offers static rubrics, deterministic computation-based metrics like ROUGE and BLEU where ground truth exists, and custom Python functions, so you are not forced into model-based judging when a cheap check would do. Two things to note. It has been rebranded under the Gemini Enterprise Agent Platform, so a lot of documentation and comparison content references a name that has changed. And adaptive rubrics are themselves generated by a model, which means rubric quality varies and inherits the usual judge bias, on top of costing more inference than a fixed metric set.
Full Vertex AI Gen AI Evaluation Service review →Our verdict on Amazon Bedrock Evaluations
Bedrock Evaluations is the sensible choice for a specific buyer - the team already on Bedrock - and unremarkable for anyone else. The argument is not capability, it is boundary. Everything stays inside your AWS account and IAM perimeter, there is no new vendor, no new contract and no new security review, and evaluation is billed per job rather than as a subscription so occasional use costs very little. For a regulated enterprise that has already cleared AWS, that combination resolves in one step what a specialist tool turns into a procurement project. The recurring criticism is fragmentation, and it is fair. CloudWatch metrics for Bedrock, Bedrock Prompt Flows and Bedrock Evaluations are described as three surfaces that feel like one on paper and three in practice, and that is the characteristic experience of AWS-native tooling - each piece works, and stitching them into a coherent workflow is your job. On agents specifically, AgentCore reached GA in October 2025 but Policy and Evaluations arrived in preview in December, so the agent evaluation story is newer than the headline suggests.
Full Amazon Bedrock Evaluations review →Frequently Asked Questions
What is the main difference between Vertex AI Gen AI Evaluation Service and Amazon Bedrock Evaluations?
Vertex AI Gen AI Evaluation Service: Teams on Google Cloud running model migrations, prompt changes or fine-tuning comparisons, who want per-prompt evaluation criteria rather than a fixed metric set. Amazon Bedrock Evaluations: Teams already committed to Bedrock who want evaluation inside their existing AWS account and IAM boundary, and who value procurement simplicity over best-in-class agent tooling. Both sit in Agent Evaluation, so the decision usually comes down to billing model and deployment rather than raw capability.
Which is cheaper, Vertex AI Gen AI Evaluation Service or Amazon Bedrock Evaluations?
It depends entirely on your workload shape, because they meter differently - Vertex AI Gen AI Evaluation Service bills on no usage metering and Amazon Bedrock Evaluations bills on job. Published starting prices are Per token plus GCP compute and Per evaluation job respectively, but those numbers are not comparable until you apply them to the same traffic. Use our cost calculator to model both against your own request volume and span count.
Can I self-host Vertex AI Gen AI Evaluation Service or Amazon Bedrock Evaluations?
Vertex AI Gen AI Evaluation Service: No or paid tier only. Amazon Bedrock Evaluations: No or paid tier only. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.