LangWatch vs Vertex AI Gen AI Evaluation Service
Both are agent evaluation tools. Here is how they actually differ on price, billing model and deployment.
LangWatch
Apache-2.0 agent evaluation built around simulation - an Agent Under Test, a User Simulator and a Judge, run through pytest in CI. That architecture is the right shape for agents and almost nothing else here has it.
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.
| LangWatch | Vertex AI Gen AI Evaluation Service | |
|---|---|---|
| Category | Agent Evaluation | Agent Evaluation |
| Our rating | 5/5 | 4/5 |
| Starting price | Event-based, rates not published | Per token plus GCP compute |
| Billing meter | event | No usage metering |
| Free plan | Yes | No |
| Free self-hosting | Yes, free | No or paid tier only |
| Best for | Teams building multi-turn or multi-agent systems who need evaluation that models conversations rather than scoring single outputs, and who want it running in CI. | 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 LangWatch
LangWatch is the strongest agent evaluation tool we have found, and the reason is architectural rather than a feature list. Its scenarios pair three components - an Agent Under Test, a User Simulator Agent that plays the human, and a Judge Agent that scores the result - and run through pytest-compatible runners locally or in CI. That is the correct shape for the problem. You cannot meaningfully evaluate a multi-turn agent by scoring individual outputs, because the failures that matter are trajectory failures, and almost every other tool in this category still treats the single response as the unit. Simulating a conversation and judging the whole thing is what agent evaluation actually requires. It is Apache 2.0 at the core with genuine self-hosting, OpenTelemetry-native so instrumentation stays portable, and billed on ingested events with no per-feature charges. The gaps are honest ones. Per-event rates are not published anywhere we could verify, the ee/ modules are commercially licensed, and running simulations costs real inference since each scenario turn drives several model calls.
Full LangWatch 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 LangWatch and Vertex AI Gen AI Evaluation Service?
LangWatch: Teams building multi-turn or multi-agent systems who need evaluation that models conversations rather than scoring single outputs, and who want it running in CI. 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, LangWatch or Vertex AI Gen AI Evaluation Service?
It depends entirely on your workload shape, because they meter differently - LangWatch bills on event and Vertex AI Gen AI Evaluation Service bills on no usage metering. Published starting prices are Event-based, rates not published 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 LangWatch or Vertex AI Gen AI Evaluation Service?
LangWatch: Yes, free. 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.