NVIDIA A100 SXM4 80 GB vs NVIDIA PG506-232 Comparison

The NVIDIA PG506-232 and the NVIDIA A100 SXM4 80 GB are both professional server accelerators built on the GA100 chip and Ampere architecture, yet they are engineered for distinctly different workloads. The PG506-232 is an end-of-life, dual-slot PCIe card with 24 GB of HBM2 memory and a 165 W power envelope, while the A100 SXM4 is a high-bandwidth OAM module with 80 GB of HBM2e memory, a 400 W power envelope, and significantly higher compute throughput. Benchmark data shows the PG506-232 achieves a Geekbench OpenCL score of 225,124, placing it in the 99th percentile of all GPUs, whereas the A100 SXM4 posts a Geekbench Vulkan score of 183,725, landing in the 98th percentile; these scores reflect different test suites, making direct comparison complex, but the underlying specifications reveal a clear division of labor.

Where Each One Wins

The PG506-232 wins in scenarios where power efficiency and a compact, self-contained form factor are paramount. Its 165 W TDP is less than half of the A100 SXM4’s 400 W, and it requires only a single 8-pin EPS connector and a 450 W suggested PSU, compared to the A100’s 800 W suggested PSU and lack of onboard power connectors (relying instead on the OAM baseboard). For systems that cannot accommodate an OAM module or lack the necessary power delivery, the PG506-232’s dual-slot, 267 mm length design is the more practical choice. Furthermore, in the Geekbench OpenCL test, the PG506-232 outperforms the A100 PCIe 80 GB (a close relative of the SXM4 variant) by 8.7%, indicating that in certain compute APIs, its tuning yields a higher score despite fewer cores.

The A100 SXM4 80 GB wins decisively in raw compute and memory capacity. Its 19.49 TFLOPS FP32 performance nearly doubles the PG506-232’s 10.32 TFLOPS, and its FP16 throughput of 77.97 TFLOPS (4:1 ratio) is over seven times higher than the PG506-232’s 10.32 TFLOPS (1:1 ratio). The A100 also offers 80 GB of HBM2e memory versus 24 GB of HBM2, with a 2.04 TB/s bandwidth that is more than double the PG506-232’s 933.1 GB/s. This makes the A100 the clear winner for large-model training, high-resolution inference, and memory-bound workloads where the 3072-bit bus of the PG506-232 would become a bottleneck. The A100’s 6912 shading units, 432 TMUs, 160 ROPs, and 432 tensor cores vastly outnumber the PG506-232’s 3584 shading units, 224 TMUs, 96 ROPs, and 224 tensor cores, reinforcing its dominance in parallel compute.

FAQ

Q: Which GPU has a higher FP32 performance?

A: The A100 SXM4 80 GB delivers 19.49 TFLOPS FP32, which is 89% higher than the PG506-232’s 10.32 TFLOPS.

Q: How does memory capacity differ between the two cards?

A: The A100 SXM4 80 GB features 80 GB of HBM2e memory, while the PG506-232 has 24 GB of HBM2 memory. This is a 56 GB difference, with the A100 also offering a wider 5120-bit bus versus 3072-bit.

Q: Are both GPUs based on the same chip?

A: Yes, both use the GA100 chip from TSMC’s 7 nm process, with the same 54,200 million transistors and 826 mm² die size. Their architectures are both Ampere, and they share the same generation designation.

Q: What is the power consumption difference?

A: The PG506-232 has a 165 W TDP, while the A100 SXM4 80 GB has a 400 W TDP. The PG506-232 suggests a 450 W PSU, whereas the A100 suggests an 800 W PSU.

Q: Which GPU has a higher benchmark percentile ranking?

A: The PG506-232 ranks in the 99th percentile of all GPUs based on its Geekbench OpenCL score of 225,124. The A100 SXM4 80 GB ranks in the 98th percentile with its Geekbench Vulkan score of 183,725.

Q: Do either of these cards support display outputs?

A: No. Both the PG506-232 and the A100 SXM4 80 GB have no display outputs, as they are designed for server and compute workloads, not graphics rendering.

Head-to-Head Benchmarks

Direct head-to-head benchmark data is unavailable, but the nearest rival comparisons provide insight into relative performance. The PG506-232’s Geekbench OpenCL score of 225,124 is 8.7% higher than the NVIDIA A100 PCIe 80 GB’s average score of 207,124, suggesting that the PG506-232 can outperform an A100 variant in OpenCL workloads. However, the PG506-232 trails the NVIDIA L20 by 10.4% (L20 score 251,147) and leads the AMD Radeon PRO W7900D by 2.4% (219,827) and the NVIDIA RTX 6000D by 14.9% (195,964).

The A100 SXM4 80 GB’s Geekbench Vulkan score of 183,725 is nearly identical to the NVIDIA RTX 5000 Ada Generation’s 184,664, a 0.5% deficit. It leads the NVIDIA RTX PRO 5000 Blackwell by 0.9% (182,109) and the NVIDIA GeForce RTX 4090 D by 3.2% (178,050), but falls 1.8% short of the NVIDIA A100 SXM4 40 GB’s 187,147. These numbers indicate that the A100 SXM4 80 GB is competitive with modern workstation cards in Vulkan, while the PG506-232 excels in OpenCL against various rivals. The biggest wins each way come from specification differences: the A100’s FP32 and FP16 throughput are 1.89x and 7.56x higher, respectively, and its memory bandwidth is 2.19x greater, while the PG506-232’s lower TDP (165 W vs 400 W) represents a 58.75% reduction in power draw.

Specification Differences

The two GPUs differ substantially across every major specification category. Clock speeds: the PG506-232 has a base clock of 930 MHz and boost of 1440 MHz, while the A100 SXM4 80 GB runs at 1275 MHz base and 1410 MHz boost. Memory: the PG506-232 uses 24 GB of HBM2 with a 3072-bit bus and 933.1 GB/s bandwidth, while the A100 uses 80 GB of HBM2e with a 5120-bit bus and 2.04 TB/s bandwidth; the effective memory speed is 2.4 Gbps for the PG506-232 and 3.2 Gbps for the A100. Core counts: the A100 has 6912 shading units, 432 TMUs, 160 ROPs, and 432 tensor cores, versus the PG506-232’s 3584 shading units, 224 TMUs, 96 ROPs, and 224 tensor cores. Pixel and texture rates: the A100 achieves 225.6 GPixel/s and 609.1 GTexel/s, while the PG506-232 reaches 138.2 GPixel/s and 322.6 GTexel/s. Power and cooling: the PG506-232 is a dual-slot card with an 8-pin EPS connector and 165 W TDP, whereas the A100 is an OAM module with no connectors and a 400 W TDP. The suggested PSU is 450 W for the PG506-232 and 800 W for the A100. Dimensions: the PG506-232 measures 267 mm in length and 112 mm in height; the A100’s dimensions are not listed. Release dates differ, with the PG506-232 launching in 2021-04-11 and the A100 in 2020-11-15, though both are end-of-life.

Architecture Differences

Both cards share the same fundamental architecture: GA100 chip, Ampere generation, 7 nm process from TSMC, and identical transistor counts (54,200 million) and die size (826 mm²). The transistor density is also the same at 65.6M per mm². Neither card has ray tracing cores, and both have no display outputs or API support listed for DirectX, OpenGL, or Vulkan. The key architectural differences lie in memory technology and compute configuration. The A100 SXM4 80 GB uses HBM2e memory, a minor evolution of the HBM2 used in the PG506-232, enabling higher effective speeds (3.2 Gbps vs 2.4 Gbps) and greater capacity (80 GB vs 24 GB). The A100’s larger core configuration—nearly double the shading units, TMUs, ROPs, and tensor cores—is coupled with a different FP16 execution mode: the A100 achieves 77.97 TFLOPS FP16 via a 4:1 ratio (likely using tensor cores for FP16 accumulation), whereas the PG506-232’s FP16 is 1:1 with FP32 at 10.32 TFLOPS, indicating a simpler execution path. The A100’s OAM form factor and 400 W power envelope reflect its design for dense, high-power compute nodes, while the PG506-232’s PCIe slot and 165 W draw align with more modest, air-cooled servers. Both share the same predecessor (Tesla Turing) and successor (Server Ada), confirming their place in the same product lineage.