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Compute with Hivenet · CPU instances
CPU cloud servers from €0.035/hour.
Launch 2 to 32 vCPU for apps, APIs, agents, data processing, CI/CD, and other general compute workloads. Each Hivenet CPU instance is an isolated cloud server with AMD EPYC performance, included RAM and NVMe storage, and per-second billing with no minimum term.
From €0.035/hr
2–32 vCPU
2 GB RAM / vCPU
50 GB NVMe included
AMD EPYC
Per-second billing
Choose the vCPU you need. Pay the same rate as you scale.
Every CPU configuration costs €0.0175 per vCPU-hour. Move from 2 to 32 vCPU without changing pricing tiers or decoding a new rate structure.
2 ×
RAM - GB
NVMe storage 50 GB
Price / hour €-
Price / month* €-
€-/m
4 ×
RAM - GB
NVMe storage 50 GB
Price / hour €-
Price / month* €-
€-/m
8 ×
RAM - GB
NVMe storage 50 GB
Price / hour €-
Price / month* €-
€-/m
16 ×
RAM - GB
NVMe storage 50 GB
Price / hour €-
Price / month* €-
€-/m
32 ×
RAM - GB
NVMe storage 50 GB
Price / hour €-
Price / month* €-
€-/m
*Monthly estimates assume 730 hours of continuous use. Actual usage is billed by the second.
What is a vCPU?
A vCPU is a virtual CPU. On Hivenet CPU instances, each vCPU represents one hardware thread on an AMD EPYC processor. Each physical CPU core provides two hardware threads, so 2 vCPU correspond to one physical core.
Need more than 32 vCPU or longer-term capacity? Larger deployments and fixed-term contracts are available through Sales.
Run apps and services on CPU cloud servers without paying for GPU power.
Use Hivenet CPU instances when the job does not benefit from GPU acceleration. These cloud servers are built for applications, services, automation, development environments, data processing, and the infrastructure around AI workloads.
Web apps and APIs
Run application backends, REST and GraphQL APIs, microservices, internal tools, and other server-side workloads.
AI agents and orchestration
Run agent runtimes, tool execution, workflow engines, model routers, API gateways, and services that coordinate AI systems.
Data processing
Handle ETL, data cleaning, tokenization, preprocessing, transformations, and other CPU-heavy stages in your data pipeline.
Development and CI/CD
Create development and staging environments, run automated builds and tests, or spin up temporary compute for individual projects.
Background jobs
Run queues, workers, schedulers, automation, crawling, and batch jobs without paying for GPU resources you do not need.
Retrieval and lightweight ML
Run retrieval services, search indexes, feature engineering, classical machine learning, and smaller workloads that do not benefit from GPU acceleration.
CPU compute without complicated pricing.
Pick the instance size, choose where it runs, and pay for the time you use. Hivenet keeps the basic choices visible instead of burying them in pricing tiers and add-ons.
One rate per vCPU
CPU pricing scales directly with instance size. RAM and 50 GB of NVMe storage are included.
Pay by the second
Usage is charged by the second from prepaid Compute credits, with no minimum term for self-serve instances.
AMD EPYC server hardware
Run CPU workloads on AMD EPYC processors with DDR5 memory and local NVMe storage.
Control your own virtual machine
Each instance runs as an isolated VM with SSH access and control over your software environment.
Choose where the workload runs
Select from the Hivenet locations available when you launch. Your workload runs in the location you choose.
Keep CPU and GPU under one Compute account
Manage CPU and GPU instances through the same platform, console, organization, and credit balance.
CPU or GPU: pay for the hardware the workload needs.
Most workloads do not need a GPU. AI systems often need both.
CPU instances handle application logic, APIs, agents, data processing, background services, and coordination. GPU instances handle workloads that benefit from massively parallel processing, including model training, inference, fine-tuning, and rendering.
CPU instances
GPU instances
Best for
General-purpose processing and services
Parallel and GPU-accelerated workloads
Typical workloads
Apps, APIs, CI/CD, data processing, agents
Training, inference, fine-tuning, rendering
In an AI system
Runs the services around the model
Runs the model and accelerated workloads
Hardware
AMD EPYC vCPU, DDR5, NVMe
NVIDIA RTX 5090 with vCPU and RAM
Pricing unit
Per vCPU-hour
Per GPU-hour
Entry price
€0.035/hour for 2 vCPU
€0.75 / GPU-hour
Swipe left to see more
If the workload does not benefit from GPU acceleration, start with CPU. Move to GPU when the job depends on GPU libraries, model execution, or highly parallel processing.
Keep CPU, GPU, inference, and storage on Hivenet.
Build more of the workload on one platform instead of splitting compute, inference, and data across separate providers.
GPU instances
Use RTX 5090 capacity for model training, inference, rendering, and workloads that benefit from GPU acceleration.
Hivenet Inference API
Use a managed model endpoint when you want Hivenet to operate the inference layer instead of running it yourself.
S3-compatible storage
Store datasets, application data, model inputs, generated outputs, and backups using S3-compatible tools.
Coming soon
Managed services are coming to Hivenet CPU.
CPU instances give you direct control over the virtual machine and software stack today. Hivenet is also building managed services on the same CPU infrastructure for workloads where you would rather have provisioning, availability, backups, monitoring, and maintenance handled for you.
We’ll publish individual services and pricing as they become available.
FAQ
CPU instance and vCPU questions
Start at €0.035/hour.
Scale when you need more.
Choose from 2 to 32 vCPU and pay by the second. For larger deployments or longer-term capacity, talk to Hivenet.
