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RTX Pro2000 Rental, Rent Pro 2000 Blackwell GPU VPS

The RTX PRO 2000 (Blackwell) is a powerhouse of efficiency, featuring 16GB GDDR7 memory and 4,352 CUDA Cores within a compact ~70W TDP envelope. Delivering ~17 TFLOPS of FP32 performance and equipped with 5th Gen Tensor Cores, it is perfectly engineered for AI-assisted workflows, CAD/3D visualization, and light AI acceleration in power-constrained environments.

Nvidia RTX Pro 2000 Blackwell 16GB GDDR7

Dedicated RTX PRO 2000 GPU VPS Pricing

Built on NVIDIA’s latest Blackwell architecture, it targets creators, engineers, and developers who need reliable performance in compact or power-constrained systems.

Professional GPU VPS- RTX Pro 2000

28GB RAM
16 CPU Cores
240GB SSD
300Mbps Unmetered Bandwidth

Once per 2 Weeks Backup
OS: Windows / Linux
Dedicated GPU: Nvidia RTX Pro 2000
CUDA Cores: 4,352
Tensor Cores: 5th Gen
GPU Memory: 16GB GDDR7
FP32 Performance: 17 TFLOPS

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$ 99.00/mo

Pro 2000 GPU Benchmarks on LLM Inference

The following data reflects the inference performance benchmarks we conducted for DeepSeek-R1 14B LLM, utilizing Ollama on Pro Blackwell GPU servers.

Nvidia RTX PRO 2000 Blackwell Specifications

The NVIDIA RTX PRO 2000 is a mid-range professional GPU designed for modern workstations that require efficient AI acceleration, professional graphics performance, and low power consumption.

Specifications

GPU Microarchitecture

Blackwell

Memory Bandwidth

~288 GB/s

CUDA Cores

4,352

Tensor Cores

136, 5th Generation

Compute Capability

12.0

RT Cores

34, 4th Generation

Memory

16 GB GDDR7

Memory Bus Width

128-bit

AI Performance

Up to ~545 AI TOPS

FP32 Performance

~17 TFLOPS

FP16 Performance

~17 TFLOPS

FP64 (double)

266.2 GFLOPS

TDP

~70 W

System Interface

PCIe 5.0 x8

Display Outputs

4 × Mini DisplayPort 2.1

Video Encode / Decode

9th-Gen NVENC, 6th-Gen NVDEC

Pixel Rate

125.2 GPixel/s

Release Date

Aug 11th, 2025

Graphics Features

DirectX

12 Ultimate (12_2)

OpenGL

4.6

OpenCL

3.0

Vulkan

1.4

CUDA

12.0

Shader Model

6.8

Features of NVIDIA RTX PRO 2000 Blackwell

Built on NVIDIA’s latest Blackwell architecture, it targets creators, engineers, and developers who need reliable performance in compact or power-constrained systems.

Blackwell Architecture-Based CUDA Cores

Blackwell is NVIDIA’s latest-generation GPU architecture following Ada Lovelace (consumer) and Hopper (data-center focused). It is designed with AI acceleration and enhanced graphics/ray tracing capabilities in mind.

Advanced AI Features

5th-generation Tensor Cores support modern AI workloads, including LLM inference, AI-assisted design tools, and content generation. Optimized for low-latency, local AI inference rather than large-scale training.

Enhanced Ray Tracing

4th-generation Ray Tracing Cores accelerate physically accurate rendering and neural graphics technologies like RTX Mega Geometry. Certified drivers for professional CAD, DCC, and visualization software.

Reliable Workstation Memory

16 GB GDDR7 with ECC ensures data integrity and system stability in professional environments.

Modern Memory & I/O

Utilizes GDDR7 memory, ECC support, PCIe 5.0, and modern display standards — enabling fast data throughput and professional visualization performance.

Efficient Performance per Watt

The PRO 2000 Blackwell delivers strong performance at a low power envelope (~70 W), ideal for compact workstations while maintaining high computational efficiency.

What is Nvidia RTX Pro 2000 Server Used for?

Renting a dedicated server with RTX Pro 2000 GPU and quickly commit to projects in these scenarios.

Professional Content Creation

Ideal for: Video editing (4K/8K timelines), Motion graphics and animation, AI-enhanced photo and video workflows, AI acceleration improves denoising, upscaling, and real-time previews.

CAD, CAE & 3D Design

Well-suited for: Architecture, engineering, and construction (AEC), Industrial and product design, 3D modeling and real-time visualization, ECC memory and certified drivers provide stability for complex projects.

AI Inference & Development

A strong choice for: Local LLM inference, AI-assisted coding and design tools, Small-scale ML inference pipelines, Not intended for large-scale model training, but highly efficient for inference workloads.

Alternatives to the GPU VPS Server with RTX PRO 2000

Multiple GPU Servers to choose from to meet your needs.

RTX A4000 Hosting

For professionals. It delivers real-time ray tracing, AI accelerated computing, and high-performance graphics to desktops.

RTX A5000 Hosting

Achieve an excellent balance between function, performance, and reliability. Assist designers, engineers, and artists to realize their visions.

RTX A6000 Hosting

High Performance for video editing & rendering,Deep Learning and Live streaming.

FAQ of NVD RTX Pro 2000 GPU VPS Hosting

Answers to more questions about the RTX Pro 2000 GPU dedicated server hosting service can be found here

What is the RTX PRO 2000 GPU VPS?

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The RTX PRO 2000 GPU VPS is a virtual private server hosting plan that includes a dedicated NVIDIA RTX PRO 2000 Blackwell GPU, giving you real GPU compute power for AI inference, graphics, and compute workloads without owning hardware.

Which Operating Systems are supported?

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Linux: Supports all major distros including Ubuntu, CentOS, and Debian, which are preferred for AI/Python environments and Docker.
Windows: Most plans include a license for Windows Server. This is ideal for RDP (Remote Desktop) and GUI-based apps like Adobe Premiere or AutoCAD.

Do I get full control of the server?

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You generally have root or administrator access, meaning you can install your own software, frameworks, containers, development tools, and drivers as needed — ideal for custom workflows.

Is the GPU "Dedicated" or "Shared"?

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On GPU-Mart’s Professional VPS plans, the GPU is typically Dedicated. GPU VPS usually implies PCIe Passthrough, meaning you have 100% of that physical card's power and VRAM dedicated to your virtual machine.

Who is this GPU VPS best suited for?

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This RTX PRO 2000 VPS is designed for: AI inference & small ML workloads, Development, testing, and light production tasks. It’s not primarily intended for large-scale model training or very heavy rendering compared to more powerful GPU instances, but it provides a strong balance of performance, memory, and cost.