Vendor-independent comparison
Google Vertex AI vs AWS Bedrock — 2026.
A Gemini-first enterprise AI platform on Google Cloud versus a multi-model foundation on AWS. The choice usually follows your data plane.
Side-by-side
Feature and fit comparison.
| Dimension | Google Vertex AI | AWS Bedrock |
|---|---|---|
| Flagship models | Gemini 2.5 Pro / Flash — 1M+ token context, native multimodal. | Claude Sonnet 4.5, Llama 3.3, Nova Pro, Titan — via one API. |
| Model garden | Gemini + Llama + Mistral + Anthropic + open-source in Vertex Model Garden. | Claude + Llama + Mistral + Titan + Nova + DeepSeek in Bedrock. |
| RAG / grounding | Vertex AI Search + BigQuery + Vector Search — deep BigQuery integration. | Bedrock Knowledge Bases on OpenSearch Serverless / Aurora / Pinecone. |
| Agents | Vertex AI Agent Builder + Agent Development Kit (ADK). | Bedrock Agents with action groups over Lambda, Step Functions, APIs. |
| Governance | Model Armor (safety, PII), Vertex Model Registry, Chronicle SIEM. | Bedrock Guardrails (PII, denied topics, grounding, jailbreak). |
| Best-fit customer | Google Cloud-native, Gemini + BigQuery-heavy programs. | AWS-native, model-choice enterprises. |
| Time-to-value | 6–12 weeks for a first Agent Builder deployment. | 6–10 weeks for a first Bedrock Agent in production. |
| Compliance | SOC 2/3, HIPAA, PCI DSS, ISO 27001, FedRAMP High. | SOC 2, HIPAA, PCI DSS, ISO 27001, FedRAMP High. |
Verdict
When each one wins.
Pick Google Vertex AI if…
- • Google Cloud is your primary cloud (BigQuery, Cloud SQL, GKE).
- • Gemini (1M+ context, multimodal, long-video) is strategic for your use cases.
- • Vertex AI Agent Builder + Search fit your agent architecture.
- • Vertex Model Garden gives you Gemini + Llama + Mistral + Anthropic on one control plane.
Pick AWS Bedrock if…
- • You are AWS-standardized (S3, Redshift, Aurora, OpenSearch, IAM).
- • Model choice across Claude, Llama, Mistral, Titan, Nova matters.
- • Bedrock Guardrails, Knowledge Bases and Agents fit your governance.
- • Provisioned throughput and PrivateLink are hard requirements.
FAQ
Questions buyers ask us.
- Which has better models?
- Depends on the workload. Gemini leads on long-context and video; Claude (on Bedrock) leads on coding and complex reasoning; Llama 3.3 is competitive on both platforms.
- Which is cheaper?
- For long-context / multimodal workloads Gemini pricing is often lower per token. For reasoning-heavy agent workloads, Claude on Bedrock can be more cost-effective. TCO depends on workload mix.
- Can we run both?
- Yes for specific model access — but governance and observability doubles. Pick a primary tied to your data plane.
Fixed-scope evaluation
A defensible recommendation — in 2 weeks.
We run a fixed-scope evaluation against your requirements, integrations and TCO — and hand your team a written recommendation with a 3-year cost model.