Dedicated GPU VM with RTX A2000 12GB
A single-tenant GPU virtual machine for AI inference, ML experiments, CUDA workloads, containers, and private GPU-accelerated services. You get root access and manage the software stack.
220,00 €
Elektronicke dodanie cloudovej sluzby
Sluzby sa zriaduju elektronicky po platbe a onboardingu. Fyzicka doprava sa neuctuje.
Agents can read product data and request quotes through the public API. Commit actions such as payment or order placement require human confirmation.
EU infra s globalnym pristupom
Zakaznicke sluzby bezia primarne na infrastrukture v EU/EHP. Zakaznici mimo Europy vratane USA mozu objednavat, ale treba pocitat s cezhranicnou latenciou. Dostupnost je vylucena pre sankcionovane alebo zakazane jurisdikcie.
Kredit a refundy
Predplateny kredit mozno pouzit na buduce opravnene sluzby. Platby su nevratne okrem pripadov, ked to vyzaduje povinne pravo alebo CLI & Open vyslovne pisomne suhlasi.
Preco to kupit
This product is a dedicated GPU server, not a managed AI application. CLIopen provisions the VM, host infrastructure, network reachability, and the assigned RTX A2000 12GB GPU. The customer receives root access and is responsible for the operating system configuration, CUDA stack, containers, AI frameworks, model downloads, application code, prompts, updates, and security inside the VM.
Co ziskas
- Full RTX A2000 12GB assigned to one customer VM.
- Root access included for CUDA, Docker, AI frameworks, and custom workloads.
- Configurable vCPU, RAM, encrypted 3x replicated NVMe disk, public IPs, backup retention, and archive retention.
- Ubuntu 24.04 LTS is the supported default operating system image.
- Support covers VM availability, network reachability, and host infrastructure, not customer-installed AI software.
What is included
- Dedicated RTX A2000 12GB GPU assigned to the VM.
- Configurable CPU, RAM, encrypted 3x replicated NVMe disk, public IPs, backup retention, and archive retention before checkout.
- Ubuntu 24.04 LTS default image and root access handoff after provisioning.
Customer responsibility
- CUDA, Docker, NVIDIA runtime, PyTorch, Ollama, vLLM, llama.cpp, and other software inside the VM.
- Model downloads, licenses, datasets, prompts, application code, users, firewall choices, updates, and security inside the guest OS.
- Debugging customer-installed AI applications unless ordered separately as paid professional services.
Good fits
- Private AI inference and model-serving experiments.
- GPU-accelerated containers, ML development, document processing, embeddings, and automation labs.
- Teams that want root access and accept responsibility for the software stack.
Configure a dedicated GPU VM
Choose hostname, CPU, RAM, encrypted NVMe disk, public IPs, backup retention, archive retention, and SSH access. The full RTX A2000 12GB GPU is dedicated to the VM.
Configure GPU VM