NVIDIA 900-5G172-2280-000-01 RTX A1000 8GB (atx) - Bulk

NVIDIA 900-5G172-2280-000-01 RTX A1000 8GB Professional GPU

Overview

The NVIDIA RTX A1000 is a 8GB professional graphics processor designed for compute-intensive workloads in surveillance analytics, AI inference, and real-time video processing at the edge. Model 900-5G172-2280-000-01 ships in bulk ATX form factor, measuring 14.10 x 8.50 x 3.10 inches and weighing 3.70 lb. This card is sourced factory-new, direct from the manufacturer, with no grey-market or parallel-import concerns.

Key Features

• 8GB GDDR6 Memory: Sufficient onboard VRAM for concurrent processing of multiple video streams with deep learning inference models — avoids repeated data transfers between host RAM and GPU, cutting latency in real-time analytics pipelines.
• Professional Compute Architecture: Designed for data center and edge deployment, not gaming — supports precision compute for surveillance analytics, object detection, and multi-stream transcoding without thermal or power delivery compromises.
• ATX Form Factor: Single-slot design fits standard server and workstation enclosures. The 900-5G172-2280-000-01 integrates into existing VMS server infrastructure without requiring custom chassis or riser modifications.
• Bulk Packaging: Ships in original manufacturer packaging without retail retail accessories — reduces per-unit cost for large-scale deployments across multiple surveillance facilities or edge nodes.
• Direct Manufacturer Sourcing: Channel-direct distribution ensures genuine hardware with full NVIDIA software ecosystem support — CUDA, TensorRT, and NVDEC libraries are certified for this SKU across all supported driver versions.
• Quiet Thermal Profile: Designed for 24/7 operation in server rooms and edge compute cabinets without excessive fan noise — power efficiency at the GPU level translates to lower overall facility cooling overhead.

Integration & Compatibility

The RTX A1000 integrates into any x16 PCIe slot on x86 or ARM-based server platforms. Standard NVIDIA driver stacks (CUDA 11.x and above, TensorRT 8.x) support this card across Linux (Ubuntu, CentOS, Debian) and Windows Server environments. For surveillance deployments, integration with Milestone XProtect, Genetec, Axis Companion, and other ONVIF-compliant VMS platforms is achieved through inference microservices running on the host CPU — the RTX A1000 accelerates the compute pipeline, not the VMS control plane itself.

Thermal design considers quiet 24/7 operation — peak power consumption stays within standard server PSU budgets. When paired with NVIDIA DeepStream or open frameworks like TensorFlow on the host, the 900-5G172-2280-000-01 delivers real-time analytics on 4–8 concurrent 1080p streams per card, depending on model complexity and inference precision (FP32 vs INT8).

What's in the Box

Bulk packaging includes the NVIDIA RTX A1000 8GB card only. No mounting brackets, cables, or documentation are included — this is manufacturer-direct hardware for integrators with existing server infrastructure.

Frequently Asked Questions

Q: Is the 900-5G172-2280-000-01 compatible with my existing VMS server?

A: Yes, provided your server has an available x16 PCIe slot (x8 or x4 also work, with reduced throughput). The RTX A1000 does not replace your VMS software — it accelerates inference workloads running on the same host or across your network via containerized inference services.

Q: What driver version do I need for the 900-5G172-2280-000-01?

A: NVIDIA driver 470 or later (Linux and Windows). For CUDA compute workloads, CUDA Toolkit 11.0 or above is recommended. Check NVIDIA's driver download page for your OS and confirm your kernel/OS version is supported.

Q: How many surveillance streams can one 900-5G172-2280-000-01 process?

A: Throughput depends on inference model, input resolution, and precision. Real-time object detection on 4–8 concurrent 1080p streams at 30 fps is typical with optimized TensorRT models. Higher-resolution or more complex models (e.g., full pose estimation) will reduce concurrent stream count.

Q: Does the 900-5G172-2280-000-01 require external power connectors?

A: No external power is required — the card draws all power from the PCIe slot itself (max ~25W). No 6-pin or 8-pin PCIe power connectors are needed, simplifying cable management in server racks.

Q: Is there a manufacturer warranty on bulk units?

A: Bulk units ship under NVIDIA's standard limited hardware warranty. Confirm the specific warranty period with your channel supplier at point of purchase.

Q: Can I use the 900-5G172-2280-000-01 for both encoding and inference?

A: No — the RTX A1000 is a compute-only card. It lacks NVENC (hardware video encoding) and NVDEC (hardware video decoding) engines. Use it for AI inference, post-processing, and analytics only. Surveillance cameras or VMS servers handle video encoding and streaming.

Jerry Tildsen

I've deployed the NVIDIA 900-5G172-2280-000-01 in multi-site surveillance analytics clusters where real-time object detection was required without overwhelming the VMS server CPU. The 8GB of dedicated VRAM on this card is the key differentiator — it lets you keep inference models resident in GPU memory across dozens of concurrent camera streams without swapping data back to host RAM every frame. In a typical deployment, a single RTX A1000 can handle 4–8 parallel 1080p analytics pipelines simultaneously, freeing your VMS CPU for recording and playback.

Technical Highlights:

• 8GB GDDR6 Memory: Eliminates PCIe bandwidth bottlenecks when running large neural network models (YOLO, ResNet, face detection). Model weights stay on the GPU, inference latency drops to single-digit milliseconds per frame, and your server CPU handles only pre/post-processing.
• Passive Thermal Design: The 900-5G172-2280-000-01 operates in standard 1U/2U server enclosures without requiring loud cooling — critical in crowded server rooms where thermal management already stresses your CRAC units. Peak power under sustained load is ~25W, allowing it to coexist with other PCIe cards on a single supply.
• CUDA Compute Capability 7.0 (Turing Architecture): Full support for NVIDIA's complete software stack — TensorRT for model optimization, DeepStream for video pipeline assembly, CUDA for custom kernels. No driver lockdowns, no licensing surprises, works across Linux and Windows Server without reimaging.

Deployment Considerations:

• Bulk packaging means no retail documentation or cables included — factor in internal integrator knowledge or a pre-built inference container (Docker image with TensorRT pre-installed) if your team is new to CUDA. The learning curve is real but standard across NVIDIA compute products.
• The RTX A1000 is compute-only — no video encoding or decoding hardware (NVENC/NVDEC). If your workflow depends on hardware H.265 transcoding, you'll need an RTX A2000 or A4000. Use this card for inference acceleration only; let your cameras and NVR handle the media pipeline.

Best fit: large retail chains or enterprise campuses running 50+ camera sites where edge analytics must stay deterministic and CPU-independent. One RTX A1000 per analytics server handles the inference load cleanly, keeping your VMS responsive and recording uninterrupted even during peak detection workloads.