# KeepRouter vs Gemini Enterprise Agent Platform, formerly Vertex AI

> KeepRouter is the narrower choice for managed model access through a public catalog and KeepRouter credentials. Gemini Enterprise Agent Platform is the current Google Cloud product name for the platform that now includes former Vertex AI capabilities, Model Garden, Agent Studio, Agent Runtime, evaluation, tuning, and cloud governance. Use the former Vertex AI name only as a migration and search reference. [1](https://cloud.google.com/blog/products/ai-machine-learning/introducing-gemini-enterprise-agent-platform) [2](https://docs.cloud.google.com/gemini-enterprise-agent-platform/release-notes) [6](https://keeprouter.com/api/openapi.json) [7](https://keeprouter.com/models)

_Last reviewed 2026-08-15 · [Editorial review](https://keeprouter.com/editorial-policy#editorial-team)_

## Short answer

Choose KeepRouter when the job is to call a documented model through a managed API without adopting a Google Cloud model and agent platform. Choose Gemini Enterprise Agent Platform when the team needs Google Cloud projects, IAM, Model Garden, model building or tuning, Agent Studio, Agent Runtime, evaluation, observability, and regional controls. Google moved Vertex AI into Gemini Enterprise Agent Platform on 22 April 2026. A current comparison should use the new name and treat Vertex AI as a former-name query, not as a separate active product.

The overlap is model inference. The operating contracts are different. KeepRouter manages a customer-facing catalog, credentials, prepaid balance, and private upstream routing. Agent Platform is a broad Google Cloud environment for models and agents. A team can prefer either approach for sound reasons, but a flat feature score would hide the main decision.

## Decision table

| Decision | KeepRouter | Gemini Enterprise Agent Platform |
| --- | --- | --- |
| Product scope | Managed access to the models and routes published by KeepRouter | Google Cloud platform for model discovery, development, tuning, deployment, agents, evaluation, and operations |
| Setup | KeepRouter account, prepaid credit, API key, model ID, and documented endpoint | Google Cloud project, billing, enabled APIs, IAM roles, location, SDK, and selected model or agent resource |
| Model choice | Use the live KeepRouter catalog and model-specific route | Use Model Garden and current Google Cloud model documentation for Google, partner, managed open, or self-deployed options |
| Agent lifecycle | Application-owned unless another documented service is used | Agent Studio, Agent Runtime, sessions, memory, tools, evaluation, and related platform services are part of the product family |
| Governance | KeepRouter public security, privacy, key scope, and service contract | Google Cloud IAM, organization policy, networking, data controls, regions, quotas, and service-specific governance |
| Pricing review | Current KeepRouter customer price and unit are in the live catalog | Generative AI, tuning, deployment, agent, and MLOps components can have different Google Cloud pricing rules |

## The naming change affects the page architecture

Google's release notes provide a direct mapping from Vertex AI names to Agent Platform names. Vertex AI Platform became Agent Platform, Vertex AI Studio became Agent Studio, Vertex AI API became Agent Platform API, and Vertex AI Model Garden became Model Garden. The announcement says the former Vertex AI services and roadmap evolve through Agent Platform.

That creates a practical SEO rule. Publish one canonical page under the current name. A legacy /compare/vertex-ai route should redirect to this page or act only as an alias. Two indexable pages with the same decision content would split intent and leave one page factually dated.

## Where KeepRouter fits

KeepRouter is useful when the application wants a smaller purchase and integration boundary. The developer selects an available model from the [live catalog](/models), uses the endpoint listed there, and authenticates with a KeepRouter key. The application does not have to create a Google Cloud project, grant Agent Platform roles, choose a region, or operate model and agent resources.

This is not a substitute for Google Cloud governance. KeepRouter does not claim Agent Studio, Agent Runtime, Google Cloud IAM, custom training, managed endpoints, Model Monitoring, or organization policy. It is also unsuitable when data residency or procurement requires a named Google Cloud region and resource.

## Where Agent Platform fits

Agent Platform fits teams whose requirement extends beyond sending inference requests. Model Garden covers model selection and deployment patterns. Agent Studio and Agent Runtime cover agent construction and operation. The platform also connects to evaluation, monitoring, tuning, notebooks, IAM, networking, and Google Cloud data services. That depth is useful when the organization already governs workloads through Google Cloud.

It also creates more decisions. The quickstart requires a project, billing, the relevant API, credentials, and IAM. Model availability and quota vary by model and location. Google has also moved generative development toward the Google Gen AI SDK, so a team with older Vertex AI SDK code should treat the naming update and client migration as separate work.

## Capability boundary

Do not equate an SDK sample with universal compatibility. Google, partner, managed open, and self-deployed models can use different endpoints, parameters, regions, deployment paths, and commercial terms. Preview status can also differ across a model, SDK, or feature. Check the exact model page, quota page, pricing page, and release notes before committing an architecture.

KeepRouter's compatibility is model-scoped as well. A listed OpenAI or Anthropic compatible route covers the documented request shape for that model. It does not reproduce Google Cloud projects, tuning jobs, grounding products, agent sessions, or every provider-native field.

## Move from Agent Platform to KeepRouter

1. Inventory model IDs, project and location settings, endpoint types, Google Gen AI SDK features, tools, grounding, tuning, safety configuration, and agent resources.
2. Separate plain inference calls from Google Cloud services. Agent Runtime, tuning jobs, managed endpoints, evaluation pipelines, and data integrations do not move with a base URL.
3. Select an independently suitable KeepRouter model and documented route. Do not treat a matching family name as proof of matching revision or behavior.
4. Replace Google authentication with a scoped KeepRouter key and remove project, location, publisher, and deployment fields that are not in the KeepRouter contract.
5. Test output, tools, streaming, safety behavior, usage, errors, token limits, and billing evidence on representative prompts before retiring Google resources.

## Move from KeepRouter to Agent Platform

1. Choose the Agent Platform product path first: managed API model, partner model, managed open model, self-deployed model, or agent resource.
2. Create the Google Cloud project and billing setup, enable required APIs, grant least-privilege IAM, and select supported regions.
3. Map each KeepRouter model requirement to the exact Google model or deployment ID and the recommended current SDK.
4. Rebuild secrets, quotas, monitoring, cost attribution, safety settings, and any agent state. KeepRouter credits and private routing do not transfer.
5. Validate SDK responses, streaming, tools, errors, quota exhaustion, regional failover rules, and data handling before production traffic moves.

The [best AI gateways page](/compare/best-ai-gateways) separates managed routers from cloud platforms. The [managed versus self-hosted guide](/compare/managed-vs-self-hosted-ai-gateways) and [evaluation framework](/blog/evaluate-ai-gateway) help turn this platform choice into a testable plan.

## Frequently asked questions

### Is Vertex AI still the current product name?

No. Google announced on 22 April 2026 that Vertex AI is part of Gemini Enterprise Agent Platform and published a mapping to the new Agent Platform names.

### Should a Vertex AI comparison have a separate URL?

Use one canonical comparison under the current name. A legacy Vertex AI URL can redirect to it so old search intent is preserved without duplicating the content.

### Does KeepRouter replace Model Garden or Agent Runtime?

No. KeepRouter exposes its documented model API and catalog. Model Garden, Agent Runtime, tuning, evaluation, and Google Cloud governance are separate platform capabilities.

### Can I move by changing only the base URL?

Only a narrow text call may be that simple. Projects, locations, model IDs, tools, grounding, agent state, streaming, errors, and authentication require explicit mapping and tests.

### Which option has more models or lower prices?

Catalogs and prices change. Compare the current official catalog and price unit for the exact model and deployment path, then evaluate the same workload without turning the result into a universal ranking.

## Sources reviewed

_Sources last reviewed 2026-08-15_

1. [Gemini Enterprise Agent Platform announcement](https://cloud.google.com/blog/products/ai-machine-learning/introducing-gemini-enterprise-agent-platform)
2. [Agent Platform release notes and naming map](https://docs.cloud.google.com/gemini-enterprise-agent-platform/release-notes)
3. [Agent Platform models quickstart](https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/start)
4. [Agent Platform quotas and limits](https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/quotas)
5. [Agent Platform generative AI pricing](https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing)
6. [KeepRouter OpenAPI](https://keeprouter.com/api/openapi.json)
7. [KeepRouter models and pricing](https://keeprouter.com/models)

## Related guides

- [Best AI gateways by use case](https://keeprouter.com/compare/best-ai-gateways.md)
- [Managed vs self-hosted AI gateways](https://keeprouter.com/compare/managed-vs-self-hosted-ai-gateways.md)
- [OpenRouter alternatives](https://keeprouter.com/compare/openrouter-alternatives.md)
- [Multimodal model APIs](https://keeprouter.com/features/multimodal-models.md)
- [How to evaluate an AI gateway with a proof-based scorecard](https://keeprouter.com/blog/evaluate-ai-gateway.md)
- [models](https://keeprouter.com/models.md)

## Separate inference from platform dependencies

Map one current Agent Platform workload to a documented KeepRouter model, then list every Google Cloud service that must remain outside the model call.

[Create a free key](https://keeprouter.com/login?returnTo=%2Fconsole%2Fkeys%3Fmodel%3Dfree) · [Live models and pricing](https://keeprouter.com/models.md)