Private LLM hosting vs DigitalOcean GPU Droplets
We rent DGX Sparks, so weigh that against everything below. DigitalOcean is a large general-purpose cloud platform, well known for simple CPU Droplets, managed databases, and app hosting, that also sells GPU Droplets as one product line among many. That breadth is the appeal: one account, one bill, GPU capacity next to whatever else you already run there. A DGX Spark takes the opposite approach: one machine, operated by GPUwerk directly, built specifically for LLM inference rather than as a line item in a broader catalog.
Side by side
| DigitalOcean GPU Droplets | Dedicated DGX Spark (GPUwerk) | |
|---|---|---|
| What it is | A GPU instance type inside a large general-purpose cloud platform, sold alongside CPU Droplets, Kubernetes, databases, and app hosting. | A single-purpose GPU host: one dedicated DGX Spark, rented by the hour, built around unified memory for inference. |
| Who operates the hardware | DigitalOcean, across its own data center regions. | GPUwerk directly, in a data center we control in Prague. |
| GPU model and specs | Varies by Droplet tier and card; check DigitalOcean's current GPU Droplets 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 | Multiple global regions; GPU Droplet 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 DigitalOcean's own terms and data processing agreement; review those directly for the specifics of GPU Droplet 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 DigitalOcean's own GPU Droplets 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 | DigitalOcean'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 Droplet, 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:
DigitalOcean GPU Droplets. Priced per hour by GPU tier and card count, published on DigitalOcean's own pricing page and changing over time by region and configuration. A fair dollar comparison needs the specific Droplet tier you'd actually run, so check DigitalOcean's current GPU Droplets 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-service 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 DigitalOcean'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 GPU Droplet, 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 a GPU Droplet may need re-testing on the Spark's unified 128GB pool, and vice versa.
When DigitalOcean GPU Droplets are the right choice
- You already run other infrastructure on DigitalOcean and want GPU capacity under the same account and bill.
- You need a specific GPU model or card count that DigitalOcean'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 instance types.
- EU data residency and a standard GDPR DPA are requirements, not nice-to-haves.
FAQ
Does DigitalOcean offer GPU instances for LLM hosting?
Yes, DigitalOcean sells GPU Droplets as part of its general cloud platform, alongside its much larger CPU Droplet, managed database, and app platform lineup. Which GPU models, regions, and rates are on offer changes over time, so check DigitalOcean's current GPU Droplets pricing page directly before comparing.
Is DigitalOcean a good alternative to a DGX Spark for running an LLM?
It depends on what you need. DigitalOcean's GPU Droplets are a general cloud provider's GPU offering, useful if you already run other infrastructure there and want everything 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 consolidating with an existing DigitalOcean footprint matters more than a purpose-built inference box, DigitalOcean is worth checking; otherwise weigh the two on hardware fit.
Is a Spark cheaper than a DigitalOcean GPU Droplet?
It depends on the specific Droplet tier and GPU model you'd compare against, since DigitalOcean prices GPU Droplets 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 DigitalOcean's current GPU Droplets pricing for the tier you'd actually need before comparing.
Does DigitalOcean host GPU Droplets in the EU?
DigitalOcean operates multiple regions including some in Europe, but GPU Droplet 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. DigitalOcean's GPU Droplet pricing and availability are not something GPUwerk can verify or restate; check DigitalOcean's own site directly.