Private LLM hosting vs Vultr Cloud GPU
We rent DGX Sparks, so weigh that against everything below. Vultr is a large general-purpose cloud platform with data centers across many regions, known for straightforward cloud compute, bare metal, and managed Kubernetes, that also sells Cloud GPU instances as one line among many. The appeal is regional reach and instance variety under one account. A DGX Spark takes a narrower approach: one machine, operated by GPUwerk directly, built specifically for LLM inference rather than as a tier in a broad catalog.
Side by side
| Vultr Cloud GPU | Dedicated DGX Spark (GPUwerk) | |
|---|---|---|
| What it is | A GPU instance type inside a large general-purpose cloud platform, sold alongside standard cloud compute, bare metal, and managed Kubernetes. | A single-purpose GPU host: one dedicated DGX Spark, rented by the hour, built around unified memory for inference. |
| Who operates the hardware | Vultr, across its own global data center regions. | GPUwerk directly, in a data center we control in Prague. |
| GPU model and specs | Varies by instance tier and card; check Vultr's current Cloud GPU page for what's on offer, since lineup and availability change. | NVIDIA DGX Spark: Grace Blackwell, 128GB unified memory, the same specification on every node. |
| Region | Many global regions, several in Europe; GPU instance availability by region varies, so check current availability for the EU specifically. | EU-Central (Prague), exclusively. One location, no region selection to get wrong. |
| Who can see your data | Governed by Vultr's own terms and data processing agreement; review those directly for the specifics of GPU instance handling. | Nobody at GPUwerk. Our DPA states GPUwerk "hosts the machine but does not access, read, copy, index, or analyse the content of the controller's instance." |
| Pricing model | Per-hour by GPU tier and card count, published on Vultr's own Cloud GPU pricing page and subject to change; check it directly for a current number. | Per hour, billed per minute: $0.79/hour on-demand, $0.59/hour for a customer-requested stop that holds your reservation. One rate regardless of workload, per pricing. |
| Contracts and DPA | Vultr's standard terms and DPA, applying across its whole platform; check current terms for GPU-specific clauses. | A standard GDPR Article 28 DPA published free at /legal/dpa, no negotiation required. Sub-processor list at /legal/sub-processors states none are engaged for instance workloads. |
| What you operate yourself | OS, model server, monitoring, backups, same as any general-purpose cloud instance, just with a GPU attached. | The same: OS, model server, any RAG or agent layer, monitoring, backups. GPUwerk keeps only a recovery copy of /workspace for hardware failures, refreshed roughly every six hours; it is not a backup service, so that responsibility is entirely yours. |
The worked cost example
Take a workload that runs inference continuously across a full month. Two ways to serve it:
Vultr Cloud GPU. Priced per hour by GPU tier and card count, published on Vultr's own pricing page and changing over time by region and configuration. A fair dollar comparison needs the specific instance tier you'd actually run, so check Vultr's current Cloud GPU pricing for that number rather than trusting a figure repeated secondhand here.
Dedicated Spark. At $0.79/hour, running continuously for a 730-hour month costs 730 × $0.79 = $576.70, flat, at one known rate from one known operator. If you hold the reservation instead of running it, the held rate drops that to 730 × $0.59 = $430.70.
A large multi-region cloud provider can be cheaper or more expensive than a single dedicated machine, and that depends entirely on the GPU tier, region, and commitment terms you'd pick on their platform. Check Vultr's current numbers for the configuration you'd actually run before deciding either way.
Migration path
Both are bare GPU instances with root access, so migration is mostly re-deploying your own stack. Serve a model through vLLM on a Spark and a similarly configured Vultr instance, and both expose an OpenAI-compatible endpoint from vLLM itself, not from the underlying provider. Put LiteLLM in front of either for request logging and key management. A model sized for a specific card's VRAM on Vultr may need re-testing on the Spark's unified 128GB pool, and vice versa.
When Vultr Cloud GPU is the right choice
- You need GPU capacity across multiple global regions and want it under one account with your other Vultr infrastructure.
- You need a specific GPU model or card count that Vultr's current lineup covers and a Spark's fixed configuration doesn't.
- Committing to a single EU-hosted operator matters less than staying inside a familiar general-purpose platform.
When a dedicated Spark is the right choice
- You want a machine built specifically for LLM inference rather than a GPU tier bolted onto a general-purpose cloud.
- A consistent specification across every node matters more than a wide catalog of regions and instance types.
- EU data residency and a standard GDPR DPA are requirements, not nice-to-haves.
FAQ
Does Vultr offer GPU instances for LLM hosting?
Yes, Vultr sells Cloud GPU instances as part of its broader cloud compute platform, which also includes standard cloud servers, bare metal, and managed Kubernetes. Which GPU models and regions are on offer changes over time, so check Vultr's current Cloud GPU pricing page directly before comparing.
Is Vultr a good alternative to a DGX Spark for running an LLM?
It depends on what you need. Vultr's Cloud GPU is a general cloud provider's GPU offering, useful if you want a wide choice of regions and instance types under one account. A dedicated DGX Spark is a single machine built specifically for LLM inference, with 128GB of unified memory, operated by GPUwerk directly in EU-Central. If instance variety and an existing Vultr footprint matter more than a purpose-built inference box, Vultr is worth checking; otherwise weigh the two on hardware fit.
Is a Spark cheaper than Vultr Cloud GPU?
It depends on the specific instance tier and GPU model you'd compare against, since Vultr prices Cloud GPU by card and configuration on its own pricing page, which changes over time. A dedicated Spark costs $0.79/hour flat, one number regardless of workload. Check Vultr's current Cloud GPU pricing for the tier you'd actually need before comparing.
Does Vultr host GPU instances in the EU?
Vultr operates data centers across many regions including several in Europe, but GPU instance availability by region varies and changes; check their current site for which regions carry GPU capacity. A GPUwerk Spark is fixed in EU-Central, Prague, with no region selection because there is only the one machine.
GPUwerk's own figures on this page ($0.79/hour, $0.59/hour, $576.70/month) come from our published pricing. Vultr's Cloud GPU pricing and availability are not something GPUwerk can verify or restate; check Vultr's own site directly.