NVIDIA PG506-232

The NVIDIA PG506-232 is a server-oriented Ampere architecture card built on the GA100 chip. It occupies a peculiar middle ground in the lineup, pairing a high-end compute die with a reduced feature set and no display outputs. This analysis focuses strictly on its measurable specifications and how they translate to practical expectations for compute workloads, using only the provided data.

Benchmark Performance

The PG506-232’s raw compute specifications are defined by its GA100 die, which is manufactured on a 7 nm process at TSMC. The card features 3,584 shading units, 224 texture mapping units, and 96 raster output processors. Clock speeds are set to a base of 930 MHz and a boost of 1440 MHz, which yields a peak FP32 performance of 10.32 TFLOPS. The data also shows a 1:1 ratio for FP16 performance, meaning the card also delivers 10.32 TFLOPS for half-precision workloads. This is a notable characteristic, as many architectures halve FP16 throughput, but here the compute capacity is consistent across both precisions.

In terms of rasterization throughput, the pixel rate is 138.2 GPixel/s and the texture rate is 322.6 GTexel/s. These figures are modest for a chip of this size, reflecting that the GA100 die is optimized for compute rather than traditional graphics rendering. The card’s percentile ranking stands at 50 out of all GPUs, which places it in the dead center of the performance distribution. However, it is critical to note that this percentile is based on an average benchmark score of zero; the benchmark database contains no actual workload scores for this part. Therefore, the percentile is a positional placeholder rather than a reflection of measured performance. Without nearest rival data or benchmark scores in the FACT PACK, the only defensible comparative statement is that the PG506-232 is positioned as a mid-pack performer by its percentile, with its true application performance being entirely dependent on the software’s ability to utilize its specific compute resources. The 10.32 TFLOPS FP32 figure is the single most concrete performance metric available, and it serves as the reference point for any workload estimation.

Power and Cooling

The thermal design power for the PG506-232 is rated at 165 W. This is a surprisingly low figure for a card with 54,200 million transistors on an 826 mm² die, indicating that the clock speeds are heavily constrained to meet this power envelope. The recommended power supply for a system housing this card is 450 W, which is a modest requirement given the card’s compute potential. Power delivery is handled through a single 8-pin EPS connector, a standard used primarily in server platforms rather than the 8-pin PCIe connectors common on consumer graphics cards; builders must ensure their power supply and cabling support this specific connector type.

The cooling solution is a dual-slot design, which is standard for this class of hardware. The card’s physical dimensions are 267 mm in length and 112 mm in height, fitting within typical server chassis constraints. The production status is listed as end-of-life, and the release date is April 11, 2021. Given the 165 W TDP, the dual-slot cooler is likely adequate for the task, but the lack of display outputs means the card is intended exclusively for rack-mounted compute nodes where airflow is managed by the chassis. The practical implication is that system integrators should verify that their 450 W PSU has a dedicated 8-pin EPS lead, as adapters from PCIe to EPS are not universally reliable under sustained load.

Ray Tracing and Feature Set

The PG506-232 does not include dedicated ray tracing cores, as the rtCores field is null in the specification data. This is a defining characteristic of the GA100 die, which prioritizes tensor and vector compute over the RT acceleration found in consumer Ampere cards. Consequently, any workload that relies on hardware-accelerated ray tracing will not benefit from dedicated silicon on this card. The feature set is instead built around 224 tensor cores, which are present and accounted for. These tensor cores are the primary accelerators for AI and deep learning tasks, including matrix operations and inference workloads.

The API support is effectively absent for graphics purposes: the DirectX, OpenGL, and Vulkan fields are all null. This reinforces that the card is not designed for graphical output or gaming. The card has no display outputs at all, making it a pure compute accelerator. The architecture is Ampere, which is the generation preceding Server Ada, and it follows the Tesla Turing line. For practical purposes, the PG506-232 is a compute-only device: it will handle FP32 and FP16 math via its shading units, and it will accelerate tensor operations via its 224 tensor cores, but it will not render frames, run graphics APIs, or process ray-traced scenes. The inclusion of tensor cores without RT cores is a clear signal that the target market is scientific computing and machine learning, not visualization.

FAQ

Q: Does the PG506-232 support DirectX or Vulkan for gaming?

A: No. The API fields for DirectX, OpenGL, and Vulkan are all listed as null, and the card has no display outputs, making it unsuitable for any graphics rendering tasks.

Q: What is the benefit of the 224 tensor cores?

A: The 224 tensor cores are dedicated to accelerating matrix math, which is essential for AI inference, deep learning training, and other dense linear algebra operations. They provide a distinct compute path separate from the standard shading units.

Q: Can this card output video to a monitor?

A: No. The display outputs field is explicitly listed as "No outputs," confirming that the card cannot be used for visual display and is intended strictly for headless compute workloads.

Q: How much power does the card consume under load?

A: The TDP is rated at 165 W, and the suggested power supply for the system is 450 W. The card uses a single 8-pin EPS power connector.

Q: What is the production status of this card?

A: The production status is listed as end-of-life. It was released on April 11, 2021, and has been succeeded by the Server Ada generation.

Q: What is the FP16 performance compared to FP32?

A: The FP16 performance is 10.32 TFLOPS, which is exactly equal to the FP32 performance of 10.32 TFLOPS. The ratio is listed as 1:1, meaning the card does not lose throughput when operating on half-precision data.

How It Compares

The FACT PACK lists no nearest rivals for the PG506-232, and the benchmark array is empty. Therefore, a direct comparison against specific competing cards is impossible using the provided data. The only positional reference is the percentile of 50, which is a neutral midpoint. This lack of comparison data is itself informative: it suggests that the PG506-232 exists in a niche where direct peers are not tracked in the same database, or that its primary competition is not a single card but rather a range of server accelerators with varied specifications. The card’s 165 W TDP is low relative to many high-performance accelerators, which often exceed 300 W, but without rival names or scores, no delta percentage can be calculated. The data indicates that the PG506-232 is a mid-tier option in the broader GPU landscape, but its specific value proposition cannot be quantified against named alternatives. Builders evaluating this part must rely on its raw specs—10.32 TFLOPS FP32, 224 tensor cores, and 933.1 GB/s bandwidth—and compare them manually to whatever other server cards they are considering, as the database provides no automated comparison here.

Memory Subsystem

The memory configuration is one of the strongest aspects of the PG506-232. It is equipped with 24 GB of HBM2 memory, connected via a 3072-bit bus. This wide interface enables a peak memory bandwidth of 933.1 GB/s. This is a substantial bandwidth figure, which is critical for memory-bound compute workloads such as large matrix multiplications, data processing, and certain scientific simulations. The memory clock operates at 1215 MHz, translating to 2.4 Gbps effective. The combination of 24 GB capacity and 933.1 GB/s bandwidth means the card can hold large datasets on-die while feeding the compute units at a high rate.

For high-resolution or large-batch workloads, this memory subsystem is a key advantage. The 3072-bit bus width is significantly wider than typical consumer cards, which usually top out at 256-bit or 384-bit interfaces. This width directly translates to the bandwidth figure, and the 933.1 GB/s number is a concrete measure of how fast data can move between memory and the compute cores. In practice, a workload that fits within the 24 GB capacity will not be bottlenecked by memory transfer rates for most operations. However, the lack of display outputs means this memory is never used for framebuffer purposes; it is entirely dedicated to compute data. The HBM2 type is also notable for its energy efficiency relative to GDDR, which aligns with the card’s low 165 W TDP. Overall, the memory subsystem—24 GB, HBM2, 3072-bit, 933.1 GB/s—is the defining feature that allows the PG506-232 to function as a capable compute accelerator despite its modest clock speeds and lack of graphics features.