RTX Pro 5000 VPS GPU Hosting Pricing
Choose an RTX Pro 5000 VPS for 48GB GPU Workloads
Select a 48GB GPU VPS when your workload needs more model memory than a 24GB configuration, while remaining more cost-conscious than 80GB or 96GB GPU options.
48GB GPU VPS for LLM Inference
A 48GB GPU VPS supports LLM inference, RAG pipelines, AI agents, and quantized larger models with more memory headroom than 24GB GPUs.
RTX Pro 5000 VPS for AI Development
RTX Pro 5000 VPS resources support model evaluation, fine-tuning, computer vision, data science, and dedicated development environments with exclusive GPU access.
RTX Pro 5000 Hosting for Rendering
RTX Pro 5000 hosting supports 3D rendering, visualization, video processing, and GPU-accelerated creative workflows that benefit from Blackwell graphics and 48GB of GDDR7 memory.
RTX Pro 5000 Benchmark Results for LLM Inference
Pro 5000 GPU Benchmark with Ollama 0.13.5
| Models | gpt-oss | deepseek-r1 | deepseek-r1 | deepseek-r1 | gemma3 | llama3.3 | qwen3 | qwen2.5 |
|---|---|---|---|---|---|---|---|---|
| Parameters | 20b | 14b | 32b | 70b | 27b | 70b | 32b | 72b |
| Size (GB) | 14 | 9 | 20 | 43 | 17 | 43 | 20 | 47 |
| GPU UTL | 61% | 75% | 85% | 93% | 78% | 91% | 90% | 93% |
| Eval Rate (tokens/s) | 175.26 | 110.01 | 53.53 | 26.07 | 51.10 | 26.05 | 47.58 | 23.72 |
Note: The models are all from the Ollama library. For more testing data, please visit: https://www.databasemart.com/blog/ollama-gpu-benchmark-pro5000
Pro 5000 GPU Benchmark with vLLM
| Models | Llama-3.1-8B | Qwen3-8B | gemma-3-12b-it | gpt-oss-20b | DeepSeek-R1-Distill-Qwen-14B | Qwen3-14B |
|---|---|---|---|---|---|---|
| Quantization | 16 | 16 | 16 | 4 | 16 | 16 |
| Size(GB) | 15GB | 15GB | 23GB | 13GB | 28GB | 28GB |
| Request Numbers | 50 | 50 | 50 | 50 | 50 | 50 |
| Benchmark Duration(s) | 14.19 | 14.12 | 23.55 | 10.42 | 23.84 | 23.98 |
| Request (req/s) | 3.52 | 3.54 | 2.12 | 4.80 | 2.10 | 2.09 |
| Input (tokens/s) | 348.77 | 354.21 | 210.15 | 479.8 | 207.67 | 208.53 |
| Output (tokens/s) | 2113.77 | 2125.27 | 1273.66 | 2878.77 | 1258.62 | 1251.18 |
| Total Throughput (tokens/s) | 2462.54 | 2479.48 | 1483.81 | 3358.57 | 1466.29 | 1459.71 |
Note: The models are all from the Hugging Face library. For more testing data, please visit: https://www.databasemart.com/blog/vllm-gpu-benchmark-pro5000
Specifications of Nvidia RTX PRO 5000
Features of NVIDIA RTX PRO 5000 Blackwell
What is Nvidia RTX Pro 5000 Server Used for?
Professional Graphics & Visualization
Virtualization & Multi-User Workstations
Media Production & Post-Processing
AI Development & Inference
Media & Live Production
Data Science & Simulation
Alternatives to the GPU VPS Server with RTX PRO 5000
RTX Pro 4000 Hosting
RTX A5000 Hosting
RTX A6000 Hosting
FAQ of NVD RTX Pro 5000 GPU VPS Hosting
What is the NVIDIA RTX PRO 5000?
What software & drivers are supported on GPUMart?
• NVIDIA RTX Enterprise / Data Center Drivers for stability and virtualization.
• CUDA toolkit for AI frameworks (e.g., TensorFlow, PyTorch).
• Docker & container runtimes with NVIDIA GPU support.
Leave us a message when you place an order.
Is Pro5000 better for AI Training or Inference?
Inference: Its 48 GB of VRAM (Blackwell) allows it to run large models (like Llama 3 70B on Ollama) on a single card with room to spare.
Training: It is excellent for fine-tuning, but for massive "pre-training," data center GPUs (A100/H100) are usually preferred due to faster interconnects (NVLink).
What kind of workloads is hosted RTX PRO 5000 good for?
• AI inference and development — running large language models (LLMs) and deep learning inference.
• Data science and analytics — large dataset processing and visualization workflows.
• Graphics, rendering, and simulation — CAD, ray tracing, and professional design apps.
• Video encoding/decoding — advanced NVENC/NVDEC acceleration for 4K+ media.
