Offshore GPU Dedicated Servers

Our GPU dedicated server lineup features NVIDIA's professional and consumer GPU accelerators, matched with high-core-count host processors and ample system memory to feed the GPU with data. Data center GPU options include NVIDIA A4000, A5000, and A6000 cards with 16-48 GB of GDDR6 memory, offering massive CUDA core counts and FP32/FP16 performance for professional compute workloads.

For AI inference and machine learning deployment, we offer NVIDIA Tesla T4 and A10 accelerator cards optimized for low-latency inference with INT8 and FP16 Tensor Core support. These cards are designed for production AI serving — image recognition, natural language processing, recommendation engines, and real-time video analysis — with power efficiency that keeps operating costs manageable.

Consumer-grade NVIDIA RTX 3080, 3090, and 4090 cards are available for workloads where raw CUDA performance matters more than ECC memory or double-precision compute. These GPUs deliver exceptional performance-per-dollar for tasks like video transcoding, 3D rendering, and cryptocurrency mining, making them an attractive option for budget-conscious customers who need GPU acceleration.

GPU servers are essential for deploying machine learning models in production. Running inference on models like Stable Diffusion, LLaMA, Whisper, or custom TensorFlow/PyTorch models requires the parallel processing power that only GPUs provide. A single NVIDIA A6000 can handle thousands of inference requests per minute for typical vision or language models, enabling responsive AI-powered applications.

Fine-tuning and training smaller models is also practical on dedicated GPU servers. While training frontier models requires data center-scale clusters, fine-tuning existing models on custom datasets, training specialized models for specific tasks, or running hyperparameter searches can be done effectively on one or two professional GPUs. Our servers provide the compute environment for this work without the hourly rates and unpredictable availability of cloud GPU instances.

The offshore aspect of our GPU servers adds a privacy dimension that cloud GPU providers cannot match. When you run AI workloads on an AnubizHost GPU server, your training data, model weights, and inference inputs never leave your control. There is no cloud provider analyzing your API calls, no telemetry phoning home, and no risk of your proprietary model or dataset being accessed by the infrastructure provider.

Video transcoding is one of the most common GPU workloads in hosting. NVIDIA's NVENC hardware encoder can transcode video streams in real-time at a fraction of the CPU resources required by software encoding. A single RTX 4090 can simultaneously transcode dozens of video streams from one format to another, making GPU servers ideal for video hosting platforms, live streaming infrastructure, and media processing pipelines.

3D rendering benefits equally from GPU acceleration. Whether you are running Blender, Arnold, V-Ray, or OctaneRender, GPU-based rendering can reduce render times from hours to minutes compared to CPU-only approaches. Our GPU servers let you set up a remote rendering farm that you can access from anywhere, processing your rendering jobs around the clock without tying up your local workstation.

Game streaming services, remote desktop applications, and virtual workstation providers use GPU servers to deliver graphics-intensive experiences to end users over the network. Each GPU can support multiple concurrent streaming sessions, enabling you to offer cloud gaming or remote workstation access to dozens of users from a single server. Combined with our low-latency European network, the experience is responsive enough for interactive use.

Our entry-level GPU server pairs an NVIDIA RTX 3080 (10 GB) with an AMD EPYC 7313P processor, 64 GB RAM, and 1 TB NVMe storage. This configuration handles video transcoding, moderate AI inference, and 3D rendering at an accessible price point. The 10 GB VRAM accommodates most production models and rendering scenes.

Mid-range configurations include the NVIDIA RTX 4090 (24 GB) or NVIDIA A5000 (24 GB) with 128 GB system RAM and multi-drive NVMe storage. The 24 GB VRAM is enough to run larger AI models like Stable Diffusion XL, LLaMA 13B (quantized), or multiple smaller models simultaneously. These servers also excel at multi-stream video transcoding and professional rendering workflows.

Enterprise GPU servers feature NVIDIA A6000 (48 GB) or multiple GPU cards in a single chassis. Multi-GPU configurations with 2x or 4x GPUs are available for workloads that benefit from parallel GPU processing — large model inference, multi-GPU rendering, or running many smaller models simultaneously. All GPU servers include full root access, IPMI management, 1 Gbps unmetered bandwidth (10 Gbps available), and our DMCA-ignored hosting policy. Cryptocurrency payments accepted.