NVIDIA Blackwell

Dedicated server

24 GB GDDR7

GPU server with 24 GB of VRAM

NVIDIA RTX PRO 4000 Blackwell SFF Edition for AI apps, image generation, and rendering. Your own environment on a dedicated server — without buying hardware.

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24 GB of VRAM

GDDR7 with ECC for models, scenes, and GPU compute.

Dedicated server

GPU, CPU, and memory for your project — no shared environment.

64 GB RAM + NVMe

Baseline profile. CPU and storage capacity are agreed for your workload.

OS or your stack

A clean system or environment setup on request.

One GPU. Your working environment.

A baseline profile for projects that need a dedicated GPU without buying your own hardware.

Baseline configuration

NVIDIA RTX PRO 4000

Blackwell SFF Edition · 1 graphics card · 24 GB GDDR7 with ECC

GPU
1 × NVIDIA RTX PRO 4000 Blackwell SFF Edition
Video memory
24 GB GDDR7 with ECC
System memory
64 GB RAM — baseline profile
Processor
Sized for your workload
Storage
NVMe · capacity by agreement
Environment
Clean OS or setup for your task

CPU, NVMe capacity, location, network options, and setup scope are confirmed before the order. This is a baseline profile for discussion — not a stock confirmation.

Built for GPU workloads

From the first prototype to your own service. We match the configuration to the model, data, and real load.

Inference and LLMs

AI assistants, text processing, and APIs. We check model requirements, context length, and concurrent requests.

Image generation

Your own models and workflows for visual content — without relying on someone else’s shared queue.

3D and rendering

GPU rendering of scenes and visualizations in compatible apps. Scene size must fit the available resources.

Video and media

Processing, encoding, and GPU acceleration for compatible media pipelines. Stack and licenses are checked separately.

Computer vision

Image experiments, recognition, and data processing on your own infrastructure.

Development and testing

Notebooks, containers, and GPU app validation. Set up dependencies and a reproducible environment.

Choose how you start

Start with an OS. Or jump straight into your workload.

Tell us which option you need in the request. We will check Blackwell version compatibility and agree the install scope.

Full control over the install

For teams with their own stack, containers, and automation. You choose the environment and deploy the application yourself.

What to agree before go-live

  • OS distribution and version
  • Compatible NVIDIA drivers
  • Disk and network requirements

Example environment stack

  • Linux
  • SSH / root access
  • Your containers and dependencies
Discuss the environment

These are server preparation options, not preinstalled templates. Versions, licenses, timelines, and pricing are agreed separately. Customers place their own data and models unless managed setup is ordered.

4 stepsSized for your loadTerms before order

From request to a working server

First we review the workload and agree the bill of materials. Then we prepare the server under a confirmed order.

Discuss the launch
  1. 01

    Describe the task

    Models, applications, data volume, and expected load.

  2. 02

    Agree the configuration

    We check compatibility, availability, location, price, and delivery time.

  3. 03

    Choose the environment

    A clean OS or software stack prep based on the agreed scope.

  4. 04

    Get access

    After the server is prepared — access and launch of your application.

  1. 01

    Describe the task

    Models, applications, data volume, and expected load.

  2. 02

    Agree the configuration

    We check compatibility, availability, location, price, and delivery time.

  3. 03

    Choose the environment

    A clean OS or software stack prep based on the agreed scope.

  4. 04

    Get access

    After the server is prepared — access and launch of your application.

Need a different GPU configuration?

More VRAM, a different CPU, or a special stack? Tell us about the workload — we will discuss the right hardware.

Discuss the configuration

Let’s discuss your GPU project

Tell us the model, application, or task. We will clarify requirements and prepare a quote for an RTX PRO 4000 Blackwell SFF server.

+1

Configuration for your task

Sizing

We start with requirements

We match GPU, RAM, CPU, and NVMe to your application and budget.

Server Illustration

Terms

A clear quote

We agree hardware, location, delivery time, and environment setup cost.

Support

Ongoing support

We can discuss help with setup and operations. Required work is scoped separately.

FAQ

What to know before ordering a 24 GB GPU server.

  • This page covers a dedicated server with one physical GPU. The final hardware list and terms of use are fixed in the quote.
  • It depends on model size, weight format, quantization, context length, and concurrent requests. One VRAM size does not guarantee every LLM will run. Include the model in your request — we will check the requirements.
  • For selected experiments and fine-tuning methods — when the stack is compatible and resources are sufficient. Full training of large models may need a different GPU or multiple servers.
  • We can discuss a clean OS or environment setup for AI development, inference, image generation, and rendering. Scope, version compatibility, licenses, and setup cost are agreed before the order.
  • Price, availability, location, and preparation time are confirmed on request. No fixed price or instant delivery is claimed. Baseline profile: RTX PRO 4000 Blackwell SFF 24 GB, 64 GB RAM, NVMe; other parameters are agreed.
  • No. This page specifies NVIDIA RTX PRO 4000 Blackwell SFF Edition with 24 GB GDDR7 with ECC. The generation name and SFF form factor matter: specs from other RTX 4000 cards do not apply to this configuration.
GPU server RTX PRO 4000 Blackwell 24 GB | King Servers