Azure AI Foundry Evaluation vs Vertex AI Gen AI Evaluation Service
Both are agent evaluation tools. Here is how they actually differ on price, billing model and deployment.
Azure AI Foundry Evaluation
Microsoft's evaluation, red-teaming and observability layer, positioned as a production lifecycle tool rather than a model API. Charges no separate runtime fee - but Foundry Memory was still in preview as of Q1 2026.
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.
| Azure AI Foundry Evaluation | Vertex AI Gen AI Evaluation Service | |
|---|---|---|
| Category | Agent Evaluation | Agent Evaluation |
| Our rating | 4/5 | 4/5 |
| Starting price | Model inference cost only | Per token plus GCP compute |
| Billing meter | No usage metering | No usage metering |
| Free plan | No | No |
| Free self-hosting | No or paid tier only | No or paid tier only |
| Best for | Enterprises already standardised on Azure that need governance, audit trails and red-teaming around AI usage as much as they need the models themselves. | 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. |
Our verdict on Azure AI Foundry Evaluation
Azure AI Foundry is the most convincingly enterprise-shaped of the three cloud evaluation offerings, and Microsoft's own framing is the clearest signal - it presents Foundry less as a model API than as a full production lifecycle tool covering evaluation, red-teaming and observability alongside inference. That matches its buyer, which is a large organisation needing governance and audit trails around AI usage as much as it needs the models. Built-in red-teaming is genuinely unusual for a cloud platform's evaluation layer, and the pricing has one quietly good property - there is no separate runtime fee for the agent service, so you pay for model inference and tool calls rather than a per-agent-hour charge, and OpenAI models cost the same as going to OpenAI directly while gaining Azure's SLA. Two cautions. Foundry Memory was still Public Preview as of Q1 2026, so SLAs and pricing were unsettled for anyone evaluating then. And total cost can span inference, orchestration, retrieval, evaluations, observability, storage and connected Azure services, which makes a single number close to meaningless.
Full Azure AI Foundry Evaluation review →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 →Frequently Asked Questions
What is the main difference between Azure AI Foundry Evaluation and Vertex AI Gen AI Evaluation Service?
Azure AI Foundry Evaluation: Enterprises already standardised on Azure that need governance, audit trails and red-teaming around AI usage as much as they need the models themselves. 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. Both sit in Agent Evaluation, so the decision usually comes down to billing model and deployment rather than raw capability.
Which is cheaper, Azure AI Foundry Evaluation or Vertex AI Gen AI Evaluation Service?
It depends entirely on your workload shape, because they meter differently - Azure AI Foundry Evaluation bills on no usage metering and Vertex AI Gen AI Evaluation Service bills on no usage metering. Published starting prices are Model inference cost only and Per token plus GCP compute 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 Azure AI Foundry Evaluation or Vertex AI Gen AI Evaluation Service?
Azure AI Foundry Evaluation: No or paid tier only. Vertex AI Gen AI Evaluation Service: No or paid tier only. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.