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Inference

Updated on 10 September, 2025

Deploy and manage AI inference workloads on Vultrs infrastructure with optimized performance and scalability.


A process that prepares and configures a server or service for use after initial deployment.
Frequently asked questions and answers about Vultrs products, services, and platform features.

Support Documents

How Do I Regenerate My Vultr Serverless Inference API Key?

Guide to regenerating your Vultr Serverless Inference API key through the customer portal

What Is the Difference Between Serverless Inference and Traditional Model Deployment?

Comparison of serverless inference vs traditional model deployment approaches, highlighting infrastructure management and scaling differences

Can I Run Inference Workloads for Models Other than Large Language Models on Vultr Serverless Inference?

Serverless Inference currently specializes in serving large language models with optimized GPU resources and token streaming capabilities.

Can I Integrate Vultr Serverless Inference with My Existing Ml Pipeline?

Serverless Inference provides a REST API-based service that easily integrates with existing ML pipelines for model deployment and inference.

How Does Vultr Serverless Inference Optimize Latency for Real-Time GenAI Applications?

Serverless Inference minimizes latency for real-time GenAI applications through pre-initialized containers and ready GPU resources that eliminate cold start delays.

Can I Test Vultr Serverless Inference Before Committing to a Large Workload?

Serverless Inference offers a Prompt tab in the customer portal for testing and evaluating inference workloads before full deployment.

Can Vultr Serverless Inference Run Multi-Modal Models Such as LLMs with Vision Capabilities?

Serverless Inference supports multi-modal AI models combining language and vision capabilities on GPU-accelerated infrastructure.

How Do I Monitor the Usage and Cost of My Vultr Serverless Inference Subscription?

Monitoring usage metrics and costs for Vultr Serverless Inference subscriptions through the Customer Portals Usage tab

How Does Vultr Serverless Inference Leverage Vultr Cloud GPUs for Efficient GenAI Deployment?

Serverless Inference provides a managed solution for deploying generative AI models on Vultrs Cloud GPUs without infrastructure management.

How Does Vultr Handle Model Versioning and Deployment Rollbacks in Serverless Inference?

Serverless Inference supports model versioning with containerized deployments, enabling parallel version operation, A/B testing, and non-disruptive updates.

What Happens If I Exceed the Included Tokens in My Vultr Serverless Inference Subscription?

Explains the billing process for exceeding the 50 million token allocation in Vultr Serverless Inference subscriptions, detailing the overage rate of $0.0002 per 1,000 tokens.

Why Am I Not Getting High Quality Output From Vultr Serverless Inference?

Troubleshooting guide explaining how model selection impacts output quality in Vultr Serverless Inference deployments.

What Are Common Use Cases for Vultr Serverless Inference?

A concise overview of typical applications for Vultrs on-demand AI model deployment service that scales automatically without infrastructure management.

How Secure Is My Data Using Vultr Serverless Inference?

Overview of data security measures and encryption protocols implemented in Vultr Serverless Inference to protect customer information and workloads.

Is Serverless Inference Suitable for Real-Time Applications?

Serverless Inference provides low-latency AI model deployment optimized for real-time applications with minimal cold-start delays.

What Observability Tools Are Available to Manage Serverless Inference Workloads on Vultr?

Overview of observability tools for monitoring and managing Vultr Serverless Inference workloads through the portal, API, and CLI