Ewa Data Center (EWADC) is expanding its GPU infrastructure portfolio with the availability of the PNY NVIDIA RTX PRO 6000 Blackwell, one of the most powerful professional GPUs based on NVIDIA’s latest Blackwell architecture.
The RTX PRO 6000 Blackwell can now be ordered through the EWADC Sales Team and deployed as part of a dedicated GPU server or custom AI infrastructure configuration in our data center environment in Poland.
For organizations building private AI platforms, inference clusters, LLM infrastructure, agentic AI systems or high-performance computing environments, the RTX PRO 6000 Blackwell provides an attractive combination of 96 GB of GPU memory, Blackwell-generation AI performance and enterprise-class features.
96 GB GDDR7 for Large AI Workloads
One of the most important advantages of the RTX PRO 6000 Blackwell is its large memory capacity.
The PNY RTX PRO 6000 Blackwell Workstation Edition provides:
- 96 GB GDDR7 memory with ECC
- 512-bit memory interface
- up to 1,792 GB/s memory bandwidth
- 24,064 CUDA cores
- 752 Tensor Cores
- 188 RT Cores
- up to 4,000 AI TOPS FP4
- PCI Express 5.0
- 600 W maximum power consumption
The 96 GB memory capacity is particularly valuable for AI inference because it allows significantly larger models, larger context windows and larger inference workloads to remain directly in GPU memory.
For enterprise deployments, ECC-protected GPU memory also provides an additional level of reliability for long-running AI and compute workloads.
Blackwell Architecture for AI
The RTX PRO 6000 is based on the NVIDIA Blackwell architecture and introduces fifth-generation Tensor Cores designed for modern AI workloads.
Support for lower-precision AI formats, including FP4, makes the architecture particularly interesting for inference environments where throughput, memory efficiency and operating cost are important.
This makes the platform suitable for workloads such as:
- Large Language Model inference
- AI agents and coding agents
- Retrieval-Augmented Generation (RAG)
- Private enterprise AI
- Model fine-tuning and experimentation
- Computer vision
- Generative AI
- Scientific computing
- Rendering and visualization
- Video processing and AI media pipelines
Instead of using the GPU only as a graphics accelerator, organizations can build complete private AI environments around the RTX PRO 6000 Blackwell.
Example: Dual RTX PRO 6000 Blackwell AI Server
EWADC can build dedicated systems equipped with two RTX PRO 6000 Blackwell GPUs, providing a combined 192 GB of physical GPU memory.
A typical configuration can include:
- 2 × PNY NVIDIA RTX PRO 6000 Blackwell
- 192 GB total GPU memory
- 48,128 CUDA cores across two GPUs
- PCIe 5.0 platform
- AMD EPYC or Intel Xeon CPU
- High-capacity DDR5 system memory
- Enterprise NVMe storage
- High-speed network connectivity
Such a configuration creates a powerful platform for local LLM inference and private AI deployments.
Running DeepSeek-V4-Flash
One example of a workload suitable for this class of infrastructure is DeepSeek-V4-Flash.
DeepSeek designed V4-Flash as the faster and more economical member of the DeepSeek-V4 family, with support for a 1-million-token context window and a strong focus on efficient reasoning and agent workloads.
With a dual RTX PRO 6000 Blackwell configuration, organizations have 192 GB of aggregate GPU memory available across two GPUs, creating an interesting platform for appropriately quantized and distributed deployments of large AI models such as DeepSeek-V4-Flash.
The exact model configuration, quantization level, context size and inference framework determine GPU memory requirements and performance. EWADC can therefore prepare the server specifically for the customer’s intended AI workload.
Popular deployment frameworks can include:
vLLM · SGLang · Ollama · PyTorch · CUDA · Docker · Kubernetes
This allows customers to deploy their own inference APIs, AI agents, internal assistants, coding systems or private generative AI applications without depending entirely on public AI infrastructure.
An Alternative for Cost-Efficient AI Infrastructure
AI infrastructure does not always require the most expensive accelerator available on the market.
The RTX PRO 6000 Blackwell combines 96 GB of VRAM per GPU with NVIDIA’s latest Blackwell architecture, making it an attractive option for organizations looking for high-memory AI acceleration while maintaining control over infrastructure costs.
For inference-oriented environments in particular, the combination of high GPU memory capacity, modern Tensor Cores and FP4/FP8 capabilities can provide an excellent foundation for building efficient AI servers.
A two-GPU configuration provides 192 GB of aggregate GPU memory without requiring a large multi-node cluster, helping reduce infrastructure complexity for many private AI deployments.
Dedicated AI Infrastructure in Poland
EWADC can supply and integrate RTX PRO 6000 Blackwell GPUs into dedicated server configurations hosted within our infrastructure in Poland.
Customers can order either individual GPU configurations or complete custom-built AI servers.
Depending on the project, EWADC can provide:
- Single-GPU and multi-GPU servers
- AMD EPYC or Intel Xeon platforms
- High-capacity DDR5 RAM
- Enterprise NVMe storage
- High-speed network connectivity
- Dedicated public IP addressing
- BGP connectivity
- DDoS protection
- Private networking
- Kubernetes environments
- AI inference software deployment
- Managed infrastructure
The hardware can be configured around the workload rather than forcing the workload into a predefined server configuration.
Build Your RTX PRO 6000 Blackwell Server with EWADC
The PNY NVIDIA RTX PRO 6000 Blackwell is now available for customer projects at EWADC.
Whether you need a single high-memory GPU server, a dual-GPU DeepSeek deployment or a larger private AI infrastructure environment, our team can prepare a configuration based on your model, workload, storage and networking requirements.
Contact the EWADC Sales Team to request pricing and a custom RTX PRO 6000 Blackwell configuration.
Tell us which AI model or workload you plan to run, and we can help select the appropriate GPU, CPU, RAM, storage and network configuration.