Vendors · Comparison
Hugging Face Inference Endpoints vs Vertex AI Provisioned Throughput
Side-by-side comparison of Hugging Face Inference Endpoints and Vertex AI Provisioned Throughput for single-tenant LLM hosting. Deployment options, compliance, pricing, and operational fit compared.
Hugging Face Inference Endpoints
Deploys Hub models on managed instances across AWS, Azure, and GCP with public, protected, or private (intra-region AWS/Azure PrivateLink) access. Vendor docs state SOC 2 Type 2 certification and a GDPR DPA via Enterprise Hub subscription, and that payloads are not stored (logs kept 30 days). Privacy policy: data may be stored in the US.
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 Hugging Face Inference Endpoints is a Managed self-host offering; Vertex AI Provisioned Throughput is Hyperscaler dedicated.
- Compliance Both document SOC 2 Type II and GDPR DPA. Only Vertex AI Provisioned Throughput documents SOC 3 and ISO 27001.
- Data residency Neither has a verified data residency guarantee.
- Jurisdiction Both parent companies are under US jurisdiction.
- Pricing Hugging Face Inference Endpoints: Per instance-hour (CPU, GPU, and accelerator instances); dedicated inference from $0.033/hour (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
| Hugging Face Inference Endpoints | Vertex AI Provisioned Throughput | |
|---|---|---|
| Category | Managed self-host | Hyperscaler dedicated |
| Deployment models | Dedicated endpointsPublic endpointProtected endpointPrivate endpoint (PrivateLink) | Provisioned throughputSingle-zone provisioned throughput |
| Regions | US, Europe | US, Europe, Asia-Pacific |
| Compliance | SOC 2 Type IIGDPR DPA | SOC 2 Type IISOC 3ISO 27001GDPR DPA |
| Pricing model | Per instance-hour (CPU, GPU, and accelerator instances); dedicated inference from $0.033/hour | 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 | Deploys Hub models on managed instances across AWS, Azure, and GCP with public, protected, or private (intra-region AWS/Azure PrivateLink) access. Vendor docs state SOC 2 Type 2 certification and a GDPR DPA via Enterprise Hub subscription, and that payloads are not stored (logs kept 30 days). Privacy policy: data may be stored in the US. | 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 Hugging Face Inference Endpoints
Both
No overlap in deployment models.
Only Vertex AI Provisioned Throughput
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