Comparison

Amazon Bedrock vs Vertex AI

Amazon Bedrock vs Vertex AI

Amazon Bedrock offers managed access to multiple foundation models inside AWS security boundaries. Vertex AI is Google Cloud’s platform for training, deploying, and calling Gemini and other models. Choose Bedrock when AWS is your control plane; choose Vertex when Google Cloud and Gemini/enterprise Google AI are your control plane.

Last verified: apis

Quick verdict

Quick verdict: Choose Amazon Bedrock when AWS is the home cloud. Choose Vertex AI when GCP is the home cloud.

Bottom line: AWS-first model platform → Bedrock. Google Cloud-first model platform → Vertex AI.

Choose Amazon Bedrock if…

  • AWS is your cloud standard
  • You want multi-model access under AWS IAM/networking
  • Your data plane already lives in AWS

Choose Vertex AI if…

  • GCP is your cloud standard
  • You want Vertex + Gemini enterprise paths
  • Your MLOps already uses Google Cloud

Bedrock vs Vertex is cloud platform selection for generative AI. Multi-cloud is possible but expensive in complexity.

Key differences

Dimension Amazon Bedrock Vertex AI
Primary role AWS managed multi-model generative platform Google Cloud enterprise AI platform
Free access No general free plan (paid / subscription access) No general free plan (paid / subscription access)
Pricing shape Usage-based AWS billing Usage-based Google Cloud billing
Standout strength Multi-model access with AWS security controls GCP training/deployment/Gemini platform depth
Main tradeoff Not ideal if your org is GCP-native Not ideal if your org is AWS-native
Best-fit user AWS is your cloud standard GCP is your cloud standard

Strengths & limitations

Amazon Bedrock

AWS managed service to access multiple foundation models through a unified API with AWS security controls.

Best for: AWS-centric builders

Why included: Primary published apis tool in demand pair.

Strengths: Multi-model access with AWS security controls.

Limitations: Not ideal if your org is GCP-native.

Pricing: Usage-based AWS billing; model prices vary.

No free plan API available

Vertex AI

Google Cloud’s enterprise AI platform for training, deploying, and calling Gemini and other models.

Best for: GCP-centric builders

Why included: Primary published apis tool in demand pair.

Strengths: GCP training/deployment/Gemini platform depth.

Limitations: Not ideal if your org is AWS-native.

Pricing: Usage-based Google Cloud billing; model prices vary.

No free plan API available

Use cases

Concrete scenarios:

  • Existing AWS SaaS: Bedrock.
  • Existing GCP data platform: Vertex.
  • Need Claude/other models in AWS: Bedrock evaluations.
  • Gemini enterprise on GCP: Vertex.

Pricing context

Amazon Bedrock: Usage-based AWS billing; model prices vary.

Vertex AI: Usage-based Google Cloud billing; model prices vary.

We avoid unverified dollar amounts. Confirm official pricing and data-handling terms before buying.

Recommendation scenarios

Choose Amazon Bedrock if…

  • AWS is your cloud standard
  • You want multi-model access under AWS IAM/networking
  • Your data plane already lives in AWS

Choose Vertex AI if…

  • GCP is your cloud standard
  • You want Vertex + Gemini enterprise paths
  • Your MLOps already uses Google Cloud

If possible, trial both on one real workflow before standardizing.

How we compared

Editorial comparison based on official product positioning and publicly described workflows. Not a lab benchmark; no synthetic win scores. Pricing stated qualitatively when exact fees are not verified in-catalog.

Sources

FAQ

Which models are available?
Lists change—check current Bedrock and Vertex model catalogs.
Can I fine-tune?
Both support various customization paths; details differ by model.
What about Azure OpenAI?
That’s the Azure control-plane option—see Azure OpenAI vs OpenAI API.

Related comparisons

Related rankings

Related learning

← All comparisons · Comparison finder