Vendors · Comparison
Databricks Model Serving vs Vertex AI Provisioned Throughput
Side-by-side comparison of Databricks Model Serving and Vertex AI Provisioned Throughput for single-tenant LLM hosting. Deployment options, compliance, pricing, and operational fit compared.
Databricks Model Serving
Mosaic AI Model Serving deploys custom MLflow models and fine-tuned foundation models on Databricks-managed serverless compute; provisioned throughput allocates dedicated inference capacity. Trust pages list ISO 27001:2022 (including AWS single-tenant), SOC 2 Type II report on request, HIPAA options, FedRAMP Moderate/High; a standard BAA is published. DPA with SCCs published. Databricks, Inc. is headquartered in San Francisco.
Vertex AI Provisioned Throughput
Provisioned Throughput reserves Gemini and partner-model capacity in generative AI scale units (GSUs) on fixed-cost terms, including 1-week options for select models. Google Cloud docs now brand the platform Gemini Enterprise Agent Platform. Vertex AI Platform appears in Google's SOC 1/2/3 and ISO 27001 scope; public GSU price list not verified at review.
From the data
Key differences
- Category Databricks Model Serving is a Managed self-host offering; Vertex AI Provisioned Throughput is Hyperscaler dedicated.
- Compliance Both document SOC 2 Type II, ISO 27001 and GDPR DPA. Only Databricks Model Serving documents HIPAA BAA and FedRAMP. Only Vertex AI Provisioned Throughput documents SOC 3.
- Data residency Neither has a verified data residency guarantee.
- Jurisdiction Both parent companies are under US jurisdiction.
- Pricing Databricks Model Serving: Per DBU per hour by GPU instance size (e.g. A10G 20 DBU/hour); per-token Foundation Model APIs (published pricing). Vertex AI Provisioned Throughput: Per GSU (generative AI scale unit) fixed-cost term; 1-week terms for select models (publication not verified).
Generated from the verified vendor data below; sources and dates on each vendor profile.
Side by side
Capabilities compared
| Databricks Model Serving | Vertex AI Provisioned Throughput | |
|---|---|---|
| Category | Managed self-host | Hyperscaler dedicated |
| Deployment models | Custom model servingProvisioned throughputPay-per-token endpoints | Provisioned throughputSingle-zone provisioned throughput |
| Regions | US, Europe, Asia-Pacific | US, Europe, Asia-Pacific |
| Compliance | SOC 2 Type IIISO 27001HIPAA BAAFedRAMPGDPR DPA | SOC 2 Type IISOC 3ISO 27001GDPR DPA |
| Pricing model | Per DBU per hour by GPU instance size (e.g. A10G 20 DBU/hour); per-token Foundation Model APIs | Per GSU (generative AI scale unit) fixed-cost term; 1-week terms for select models |
| Public pricing | Yes | Not verified |
| Residency guarantee | Not verified | Not verified |
| Parent jurisdiction | US | US |
| Analyst note | Mosaic AI Model Serving deploys custom MLflow models and fine-tuned foundation models on Databricks-managed serverless compute; provisioned throughput allocates dedicated inference capacity. Trust pages list ISO 27001:2022 (including AWS single-tenant), SOC 2 Type II report on request, HIPAA options, FedRAMP Moderate/High; a standard BAA is published. DPA with SCCs published. Databricks, Inc. is headquartered in San Francisco. | Provisioned Throughput reserves Gemini and partner-model capacity in generative AI scale units (GSUs) on fixed-cost terms, including 1-week options for select models. Google Cloud docs now brand the platform Gemini Enterprise Agent Platform. Vertex AI Platform appears in Google's SOC 1/2/3 and ISO 27001 scope; public GSU price list not verified at review. |
Where they diverge
Deployment differentiation
Only Databricks Model Serving
Both
Only Vertex AI Provisioned Throughput
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