Private LLM hosting vs Voltage Park
We rent DGX Sparks, so weigh that against everything below. Voltage Park built its business around large on-demand pools of NVIDIA H100 GPUs, hosted in US data centers, aimed at teams training or fine-tuning models at cluster scale. If you're EU-based and need EU data residency, or you just need one machine to serve one or a few open-weight models, that's a different shape of problem than Voltage Park is built to solve. A Spark is smaller in every sense: one machine, one EU location, one flat rate.
Side by side
| Voltage Park | Dedicated DGX Spark (GPUwerk) | |
|---|---|---|
| What it's built for | On-demand rental of large H100 GPU pools, sized for training and fine-tuning jobs that need many GPUs at once. | One dedicated machine for one team's inference workload, not a training cluster. |
| GPU hardware | NVIDIA H100 GPUs, at cluster scale; check Voltage Park's current fleet and availability directly, since capacity and pricing shift with demand. | NVIDIA DGX Spark: Grace Blackwell, 128GB unified memory, one unit per instance. |
| Region | US data centers; confirm current facility locations on Voltage Park's own site, since this determines where your data physically sits. | EU-Central (Prague), on one dedicated machine, no region choice because there's only the one. |
| Who can see your data | Governed by Voltage Park's own customer agreement and data processing terms; review those directly, and note that US hosting has different legal exposure than EU hosting under GDPR. | 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-GPU-hour for H100 instances, published on Voltage Park's own site and subject to change with demand; check there for a current figure. | One flat hourly rate regardless of workload: $0.79/hour on-demand, $0.59/hour held. Per pricing. |
| Operational model | Bare GPU instances with cluster networking for multi-node jobs, aimed at teams running their own training stack. | Root SSH access to a container on the Spark. No cluster networking to configure; you run vLLM, LiteLLM, or whatever stack you choose yourself. |
The worked cost example
Take a team that wants one always-on model endpoint for internal use, no training, no cluster. On a Spark, running spark-1x continuously for a full month is 730 hours × $0.79/hour = $576.70, before tax, per pricing. Fixed, regardless of request volume or which open-weight model is loaded.
Voltage Park doesn't publish a comparable single figure for this exact scenario because its pricing is built around H100-hour rates for cluster-scale jobs, and a single-GPU inference workload isn't really the use case it's optimized for. If your workload genuinely needs multiple H100s with fast interconnect for training, Voltage Park's on-demand model can be considerably more cost-effective than assembling that scale any other way. If you need exactly one GPU-class machine for inference, want EU hosting, and don't want to think about GPU-hour rates for a cluster you're not using, the Spark's flat $576.70/month is the simpler number. Check Voltage Park's own pricing page for their current H100 rate if cluster scale is what you need.
Migration path
Model weights for open models move freely between the two: a checkpoint trained on Voltage Park's H100 cluster can be copied to a Spark and served there with vLLM, and vice versa. What doesn't move is anything built on Voltage Park's multi-node interconnect or cluster orchestration, none of which has an equivalent on a single Spark because a Spark is one machine, not a cluster.
When Voltage Park is the right choice
- You're training or fine-tuning models and need multiple H100 GPUs with fast interconnect between them.
- US hosting fits your data residency requirements, or you have no EU residency requirement at all.
- On-demand H100-hour pricing at cluster scale beats what you'd pay assembling that capacity elsewhere.
When a dedicated Spark is the right choice
- You need one machine for one team's inference workload, not a training cluster.
- EU data residency is a requirement, not a preference.
- You want a fixed, predictable hourly number with no GPU-hour cluster math to work through.
FAQ
Where does Voltage Park host its GPUs?
Voltage Park's data centers are US-based; check their current site for the specific facilities and any expansion plans, since footprint changes over time. A GPUwerk Spark is fixed in EU-Central, Prague, which matters if EU data residency is a requirement rather than a preference.
What GPUs does Voltage Park rent versus a DGX Spark?
Voltage Park's core offering has centered on large pools of NVIDIA H100 GPUs for on-demand cluster rental, sized for training and large-batch inference; check their current fleet for exact numbers. A DGX Spark is a single desktop-form-factor unit built around Grace Blackwell with 128GB of unified memory, aimed at one team running one or a few open-weight models, not multi-node training.
Is a Spark cheaper than Voltage Park?
It depends on scale. Voltage Park prices by the GPU-hour for H100 clusters and publishes current rates on its own site, which change with demand and contract length, so check there for a number you can trust. A single GPUwerk Spark runs $0.79/hour on-demand with no minimum term, a different shape of purchase: one machine, not a slice of a cluster.
Can I move a model between Voltage Park and a Spark?
Yes, for open-weight models. Weights are portable between any two Linux GPU instances. What doesn't move is any multi-GPU training setup or interconnect-dependent tooling built around Voltage Park's H100 clusters, since a single Spark is one machine with no equivalent interconnect.
GPUwerk's own figures on this page ($0.79/hour, $0.59/hour, $576.70/month) come from our published pricing. Voltage Park does not publish a single comparable per-machine rate for this scenario; its pricing is built around H100-hour cluster rates, so check Voltage Park's own pricing page directly rather than relying on a figure here.