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Hivenet vCPU instances: configurations, pricing, and use cases
Hivenet offers CPU-only Compute instances for workloads that do not need GPU acceleration. Current configurations range from 2 vCPUs with 4 GB of RAM and 50 GB of NVMe storage to 32 vCPUs with 64 GB of RAM and 800 GB of NVMe storage. Instances use prepaid credits and are billed per second while they run.
Available vCPU configurations
The current CPU-only configurations are:
- 2 vCPUs | 4 GB RAM | 50 GB NVMe SSD | 250 Mb/s | €0.035/hour
- 4 vCPUs | 8 GB RAM | 100 GB NVMe SSD | 250 Mb/s | €0.07/hour
- 8 vCPUs | 16 GB RAM | 200 GB NVMe SSD | 500 Mb/s | €0.14/hour
- 16 vCPUs | 32 GB RAM | 400 GB NVMe SSD | 1,000 Mb/s | €0.28/hour
- 32 vCPUs | 64 GB RAM | 800 GB NVMe SSD | 1,000 Mb/s | €0.56/hour
The Compute console is the source of truth for the configuration, price, region, and capacity you can launch now. See the current vCPU documentation before choosing a size.
You can stop and start a vCPU instance without losing the environment on its attached disk. Stopping releases the underlying capacity, so restarting depends on current demand and may place the workload on different hardware. A stopped instance is automatically terminated after 10 days. Review the current lifecycle rules before relying on stop and start.
vCPU vs. GPU: what fits your workload?
GPUs are designed for highly parallel workloads such as machine learning training and graphics rendering. For general-purpose computing that does not use GPU acceleration, a vCPU instance is usually the better fit.
- Control compute cost: The hourly rate is shown before launch, and running time is billed per second through prepaid credits.
- Run general-purpose workloads: vCPUs are suitable for web services, APIs, development databases, CI/CD, data-processing scripts, and background jobs.
- Use standard CPU software: Choose vCPU when the application does not depend on CUDA or another GPU-specific acceleration path.
- Plan for current capacity: Available sizes and regions can vary. Check the creation screen for what can be launched now.
Why run vCPU workloads on Hivenet?
Hivenet publishes fixed configuration rates and bills active instances per second. For on-demand instances, attached NVMe storage and network traffic are included in the compute price. The console shows the hourly rate before launch.
Compute runs on Hivenet's distributed cloud and certified provider infrastructure. Use the current GPU and CPU rental page for the maintained product path, available workload guidance, and pricing links.
Common vCPU workloads
- Startups and small teams: Run web services, APIs, development databases, and background services without paying for GPU capacity the workload does not use.
- Developers: Build, test, and deploy applications with a configuration matched to the current resource requirement.
- Automation and data work: Run CI/CD pipelines, batch jobs, preprocessing, and scripts that do not require GPU parallelism.
Ready to get started?
Review the current configuration and lifecycle guidance, then choose an available vCPU size in Compute. Billing begins when the instance runs and stops according to the documented lifecycle rules.
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