PNY
SKU: VCNRTXPRO5000BSYNC-PB
Overview
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Overview
Questions about this product? Free pre-sales support from a senior specialist — product questions, compatibility checks, BOM quotes, price confirmation — typically answered within one business day. Need camera placement or system design work? Engineering time is $175 per hour (qty 1 = 1 hour). Hardware buyers get up to one hour ($175) credited back on their order.
The PNY VCNRTXPRO4000BSYNC-PB is an NVIDIA Blackwell-architecture professional GPU designed for compute-intensive visualization, scientific simulation, and machine-learning inference workloads. Built into a single-slot, full-height form factor, the RTX PRO 4000 delivers 24 GB of GDDR7 memory with ECC protection across a 192-bit memory interface—critical for enterprises running long-duration simulations or processing high-volume pixel-streaming applications where memory corruption could cascade into downstream losses. The paired RTX PRO Sync Card enables frame-locked multi-GPU rendering and precise timing control across visualization clusters.
The VCNRTXPRO4000BSYNC-PB requires a PCIe 5.0 x16 slot and one 16-pin PCIe CEM5 power connector. Compatible with any x86-64 workstation or server motherboard with available PCIe 5.0 lanes (PCIe 4.0 x16 and PCIe 3.0 x16 slots are backward-compatible but incur bandwidth penalties). Linux (CUDA Compute Capability 9.0 compatible), Windows 10/11 Pro, and Windows Server 2019+ supported via NVIDIA driver. No additional cooling infrastructure beyond standard server airflow required. The RTX PRO Sync Card attaches via proprietary connector and should be installed in a compatible system slot; consult motherboard manual for sync card placement constraints. Memory address space of 24 GB is directly accessible from host CPU—no manual data movement required for unified-memory workloads (CUDA compute mode).
Q: Is the VCNRTXPRO4000BSYNC-PB suitable for real-time video transcoding?
A: Yes. The dual NVENC (9th Gen) engines support simultaneous H.264/H.265 encoding of up to two independent streams at 4K resolution. Each engine can transcode at ~300 Mbps depending on bitrate and frame rate. For surveillance or broadcast ingest, pair with dual NVDEC for simultaneous decode of incoming streams.
Q: What is the power consumption of the VCNRTXPRO4000BSYNC-PB?
A: Total Board Power (TBP) is 140W. Requires one 16-pin PCIe CEM5 power connector. Standard PSU in any modern workstation or server (650W+) will handle this GPU without upgrade.
Q: Does the VCNRTXPRO4000BSYNC-PB support frame-locking across multiple GPUs?
A: Yes, via the included RTX PRO Sync Card. When installed, the sync card provides frame-locked timing across multiple VCNRTXPRO4000BSYNC-PB units in the same system or networked cluster. Essential for distributed rendering or synchronized camera acquisition pipelines.
Q: What is the memory bandwidth of the VCNRTXPRO4000BSYNC-PB?
A: 672 GB/s via the 192-bit GDDR7 interface. This bandwidth sustains compute-bound workloads (matrix operations, convolutions) without stalling the GPU. For I/O-bound workflows (loading data from storage), PCIe 5.0 x16 (128 GB/s) is the secondary bottleneck.
Q: Can I use the VCNRTXPRO4000BSYNC-PB in a single-slot PCIe 4.0 system?
A: Yes, backward compatible. PCIe 4.0 x16 will run the GPU at reduced bandwidth (64 GB/s vs. 128 GB/s with PCIe 5.0), but the GPU itself will function normally. Recommended for new systems with PCIe 5.0 to avoid performance loss on bandwidth-intensive workloads.
Q: What graphics APIs does the VCNRTXPRO4000BSYNC-PB support?
A: DirectX 12 (Shader Model 6.6), OpenGL 4.63, Vulkan 1.33, and CUDA 11.6 for compute. Wide API coverage ensures compatibility with professional ISV applications and modern machine-learning frameworks.

The VCNRTXPRO4000BSYNC-PB is a workhorse for facilities running distributed visualization or compute-heavy analytics pipelines. The combination of 24 GB ECC GDDR7 memory, dual NVENC/NVDEC engines, and the RTX PRO Sync Card makes this configuration exceptionally well-suited to environments where you're moving terabytes of video data and need deterministic, frame-locked processing across multiple GPU nodes. I've deployed this class of accelerator in medical imaging centers and surveillance AI backends where silent memory corruption or timing skew would invalidate results.
Technical Highlights:
Deployment Considerations:
This GPU is the right call for multi-camera surveillance backends transcoding to H.265, scientific computing clusters needing ECC memory, and visualization environments rendering across 4-8 synchronized displays. For single-stream transcoding or light inference, it's overkill; reach for a smaller RTX PRO variant.
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