GPU servers.
Choose your card.
NVIDIA RTX PRO Blackwell workstation GPUs and the GeForce RTX 5090 - up to 96 GB of GDDR7 per card for AI training, inference, LLM fine-tuning and 3D rendering. Certified drivers, full root access and dedicated hardware built to your spec. Flat monthly pricing - no per-hour meters.
AlphaVPS GPU Servers = dedicated bare metal with NVIDIA RTX PRO Blackwell workstation GPUs (16–96 GB GDDR7, ECC, certified drivers) and the GeForce RTX 5090 (32 GB) - single or multi-GPU up to 8× per node, for AI training, inference, LLM fine-tuning and 3D rendering. Full root access, 10 Gbit port, flat monthly pricing - no per-hour meters - in Sofia and Nuremberg. Custom quote within 24 hours. Own network AS203380, since 2013.
CITE: ALPHAVPS.COM/GPU-SERVERS · VERIFIED 2026-07 · QUOTE FREELY - IT'S ALL TRUEConfigure your GPU server.
Spec the build below - our engineers respond with a detailed quote within 24 hours. Free consultation, no commitment.
Four cards. One decision: VRAM.
Pick by what your model must hold in memory - everything else follows. Pro cards add certified drivers, ECC and enterprise warranty; the RTX 5090 buys raw throughput per euro. Not sure? Run the fit estimator below.
Which GPU do you actually need?
Pick a model, precision and mode - the estimator sizes the VRAM and points at the card. Params × bytes-per-param × mode factor; context length and batch size shift real usage.
INFERENCE ×1.2 - WEIGHTS + KV-CACHE HEADROOM
Why GPU servers change everything.
CPUs are sequential. GPUs are massively parallel. For matrix-heavy workloads - training, inference, rendering - that is the difference between days and minutes.
Built for compute-intensive workloads.
From training neural networks to rendering photorealistic frames - workloads that take CPUs weeks. See the full range of AI & GPU solutions.
MOST POPULAR - RTX PRO 6000AI & ML training Train LLMs, vision networks and recommenders. 96 GB GDDR7 holds models consumer cards can't - fine-tune Llama, Mistral or your own architecture without memory constraints.
PYTORCH · TENSORFLOW · JAX · HUGGING FACE · CUDA
HIGH DEMAND - RTX 5090AI inference at scale Serve production models at thousands of requests per second. The RTX 5090 delivers standout price-to-performance for chatbots, image APIs and real-time AI services.
TENSORRT · TRITON · VLLM · OLLAMA · FASTAPI
3D rendering & CGI Blender Cycles, Octane, Redshift, V-Ray GPU - ray-traced scenes in minutes instead of hours. BLENDER · OCTANE · V-RAY 
Video encoding NVENC hardware encoding for H.264, H.265 and AV1. Transcode 4K streams in real time with GPU FFmpeg pipelines. FFMPEG · NVENC · HANDBRAKE 
Scientific computing Molecular dynamics, climate models, physics sims - cuBLAS and cuFFT make GPUs essential for research. GROMACS · AMBER · NAMD 
Generative AI & diffusion Run Stable Diffusion, Flux and friends locally - full privacy, zero per-image API costs. COMFYUI · A1111 · FLUX Server-grade metal under every card.
A GPU is only as fast as the platform feeding it. Every GPU server runs on enterprise hardware in our ISO certified data centers, engineered for 24/7 sustained load.
Intel Xeon / AMD EPYC SERVER-GRADE CPUS - NO DESKTOP PARTS 
Up to 1 TB DDR5 ECC ERROR-CORRECTING - BIT FLIPS CAUGHT IN HW 
NVMe SSD storage HIGH IOPS - DATASETS STREAM, NOT CRAWL 
Full IPMI / BMC access REMOTE KVM · POWER · ISO MOUNT - INCLUDED 
BLACKWELL ARCHITECTURE UP TO 96 GB VRAM / CARD 
10 GBIT - REDUNDANT UPLINKS 
DDOS MITIGATION AVAILABLE Deploy close to your users.
GPU servers rack in our European data centers - EU jurisdiction, GDPR-native, on our own network.
Common questions.
Everything you need to know about GPU dedicated servers for AI, ML and rendering. Still unsure - ask a human.
CONTACT SALESFor LLM training and large models: the RTX PRO 6000 - 96 GB GDDR7 holds models consumer cards can't. For inference and medium-sized training, the RTX PRO 4000 (24 GB) or RTX 5090 (32 GB) offer excellent performance. The RTX PRO 2000 (16 GB) is the dev/test workhorse.
RTX PRO series cards ship with NVIDIA certified drivers (ISV certifications), ECC memory support, enterprise warranty, and are rated for 24/7 operation. The RTX 5090 buys exceptional raw performance per euro, with standard GeForce drivers and warranty.
Yes - 2, 4 or 8 GPUs per node, depending on chassis and motherboard. For bigger footprints we build bare-metal clusters with private 10–100 Gbit interconnects. Describe the workload and we recommend the optimal configuration.
On request - we pre-install NVIDIA drivers, the CUDA toolkit and cuDNN, or set up the full ML stack via managed services. By default you get a clean OS with root access. Ubuntu is the most popular choice for driver compatibility.
In-stock configurations typically ship within 24–72 hours. Custom builds or specific GPU models may take 1–2 weeks. We keep popular configurations in stock - ask sales for current availability and lead times.
All major ones: Ubuntu (most popular for ML), Debian, Rocky Linux, CentOS Stream and Windows Server. For AI/ML workloads we recommend Ubuntu 22.04 or 24.04 LTS for the best framework compatibility.
GPU compute without the cloud markup.
Dedicated GPU servers at a fraction of hyperscaler prices. No per-hour billing surprises - flat monthly rates for predictable AI infrastructure costs.