Private LLM hosting vs CUDO Compute
We rent DGX Sparks, so weigh that against everything below. CUDO Compute runs a GPU marketplace: instances are listed from a mix of CUDO's own capacity and partner data centres in different locations, priced per GPU-hour and picked by region and GPU class. A GPUwerk Spark is one dedicated node, operated by GPUwerk directly, at a flat hourly rate.
Side by side
| CUDO Compute | Dedicated DGX Spark (GPUwerk) | |
|---|---|---|
| Business model | A marketplace: GPU capacity is listed from CUDO's own infrastructure and from data centre partners, similar in structure to Vast.ai or a cloud reseller. | A single operator. GPUwerk owns and runs the node you rent; there is no partner layer to identify. |
| Who operates the physical machine | Varies by listing: sometimes CUDO, sometimes a partner data centre. Check the specific listing for the operator before deploying anything sensitive. | Always GPUwerk, from a Prague-based fleet, no partner or reseller in between. |
| Region selection | Multiple listed locations, including European sites; availability shifts as partner capacity changes. | EU-Central (Prague), fixed, no availability shifts because there's one region. |
| Pricing model | Per GPU-hour, varying by GPU class and by which listing you land on. Check CUDO Compute's current marketplace for a figure specific to your GPU choice. | Flat $0.79/hour on-demand, $0.59/hour held rate, one price regardless of model, per pricing. |
| Hardware consistency | Depends on the listing; different partners may run different generations of the same GPU class, with different surrounding infrastructure (storage, network). | Every node is the same DGX Spark hardware: NVIDIA GB10 Grace Blackwell, 128 GB unified memory. |
| Contracts and DPA | CUDO Compute's own terms apply to the CUDO side of the relationship; a partner-operated listing may add that partner's own terms. | One GDPR Article 28 DPA, published free at /legal/dpa, no negotiation and no partner terms to track down. |
Cost, worked from GPUwerk's own numbers
A Spark held for a full 730-hour month costs $576.70 at the $0.79/hour on-demand rate, or $430.70 at the $0.59/hour held rate, straight from pricing, before tax. CUDO Compute's marketplace pricing varies by GPU class and by which listing is available at the time you deploy, so there's no single number to put next to that; check their current listings for the GPU class your model actually needs and compare the per-hour figure against the Spark rate for your expected usage pattern.
The practical question for a marketplace is less "which is cheaper" and more "which listing am I actually getting." A lower headline rate on one listing and a higher rate on another, both under the same marketplace, can reflect different partner infrastructure, not just different GPU generations. A Spark removes that variable: every node is identical hardware from one operator, so the rate you see is the rate and the hardware behind it doesn't change week to week.
When CUDO Compute is the right choice
- You want to shop across GPU classes and regions in one marketplace rather than committing to one provider's fixed lineup.
- Your workload benefits from a data-centre GPU class beyond what a Spark's GB10 chip offers.
- You're comfortable checking each listing's specific operator and terms as part of your own diligence.
When a dedicated Spark is the right choice
- You want to know exactly who operates the hardware your data touches, with one name on the DPA and no partner layer to trace.
- You want a rate that doesn't change with GPU generation, listing, or availability.
- Your inference workload fits in 128 GB unified memory and doesn't need to shop across GPU classes.
FAQ
Is CUDO Compute the company that owns the GPU hardware?
Not always. CUDO Compute operates a marketplace model, listing GPU capacity contributed by data centre partners in multiple locations, alongside its own infrastructure. Which of those applies to a given instance affects who physically operates the machine your workload runs on. Check the listing details for the specific region and operator before deploying anything sensitive.
Can I pick which country my CUDO Compute instance runs in?
CUDO Compute lets you select a region when deploying, and lists multiple locations including European sites. Confirm the exact data centre and its operator on their console for your compliance requirement, since marketplace listings can change as partner capacity comes on and off line.
How does CUDO Compute pricing compare to a GPUwerk Spark?
CUDO Compute prices GPU instances per GPU-hour, varying by GPU class and by which partner's capacity you land on, since it's a marketplace. GPUwerk charges one flat rate per Spark node: $0.79/hour on-demand, $0.59/hour held. Check CUDO Compute's current listings for your GPU class and compare against /pricing/ for your specific volume.
Is a marketplace model less secure than a single dedicated provider?
Not inherently, but it changes the diligence you need to do. On a marketplace, you're trusting whichever partner operates the specific machine you land on, and that partner's own security and data-handling practices, not just the marketplace operator's stated policy. On a GPUwerk Spark, GPUwerk operates the machine directly and states in its DPA that it does not access, read, copy, index, or analyse the content of your instance.
Can I run the same open-weight model on CUDO Compute and a GPUwerk Spark?
Yes. Open-weight models like gpt-oss, Llama, and Qwen run on any GPU with enough memory for the chosen quantisation, regardless of which cloud rents you the hardware. Throughput will differ by GPU class, so benchmark your actual model and prompt shape on each before deciding.
GPUwerk's own rates and the 730-hour monthly figures on this page come directly from gpuwerk.com/pricing. GPUwerk has not independently verified CUDO Compute's current marketplace listings, per-GPU rates, or partner locations; check their own console for figures specific to your deployment.