NVIDIA PG506-232 vs NVIDIA Tesla V100 SXM2 32 GB Comparison

Where Each One Wins

The benchmark data presents a clear and unambiguous picture: the NVIDIA PG506-232 wins the only directly comparable workload in this database, and it does so by a substantial margin. In the Geekbench OpenCL test, the PG506-232 scores 225,124 points against the Tesla V100 SXM2 32 GB's 131,696 points. That is a 70.9% advantage for the Ampere-based card, a gap that dwarfs the differences seen between either card and its nearest rivals. The V100 SXM2 32 GB, by contrast, has no benchmark win in the head-to-head comparison. Its sole available direct comparison leaves it trailing by a wide margin.

Looking at where each card sits relative to the broader GPU landscape, the PG506-232 occupies the 99th percentile among all GPUs, while the V100 SXM2 32 GB sits at the 96th percentile. The PG506-232's average benchmark score of 225,124 places it comfortably ahead of its nearest listed rival, the NVIDIA A100 PCIe 80 GB, which averages 207,124 — a 8.7% gap in the PG506-232's favor. It also beats the AMD Radeon PRO W7900D (219,827) by 2.4% and the NVIDIA RTX 6000D (195,964) by 14.9%. The only listed GPU that outpaces it is the NVIDIA L20, which scores 251,147, a 10.4% advantage over the PG506-232.

The V100 SXM2 32 GB, meanwhile, averages 137,731 across its two benchmark entries (131,696 OpenCL and 143,765 Vulkan). Its nearest rivals cluster tightly: the Tesla V100 PCIe 16 GB scores 138,063 (0.2% higher), the AMD Instinct MI100 scores 139,035 (0.9% higher), and the AMD Radeon PRO V620 scores 136,472 (0.9% lower). The AMD Radeon Pro W6800X Duo trails at 135,774, 1.4% behind. This clustering suggests the V100 SXM2 32 GB is firmly in a performance tier that the PG506-232 simply leaps over.

The wins, such as they exist, are one-sided. The PG506-232 wins the sole head-to-head benchmark. The V100 SXM2 32 GB does not win any. However, the V100's 32 GB memory capacity versus the PG506-232's 24 GB is a specification difference that could matter in memory-bound workloads, even if no benchmark in this data captures that distinction. Similarly, the V100's higher FP32 throughput (15.67 TFLOPS vs 10.32 TFLOPS) and larger shading unit count (5120 vs 3584) suggest it should be faster in raw compute tasks, yet the OpenCL result contradicts that expectation. The data, not the theoretical specifications, is what governs here.

The Verdict

The data points to a single clear conclusion: the NVIDIA PG506-232 is the stronger performer in the one benchmark where both cards have comparable results. Its 70.9% lead in Geekbench OpenCL is not a narrow margin — it is a decisive one. Anyone selecting a card strictly on the basis of this benchmark should choose the PG506-232 without hesitation.

That said, the V100 SXM2 32 GB is not without its own claims. It offers 32 GB of HBM2 memory compared to the PG506-232's 24 GB, a 33% capacity advantage. It also carries more shading units (5120 vs 3584), more texture mapping units (320 vs 224), more render output units (128 vs 96), and more tensor cores (640 vs 224). Its FP32 throughput is 15.67 TFLOPS versus 10.32 TFLOPS, and its FP16 throughput is 31.33 TFLOPS versus 10.32 TFLOPS. These are substantial specification advantages. Yet none of them translate into a benchmark win in the available data.

The V100's nearest rivals in the benchmark database all score within 1.4% of it, suggesting it is a stable, predictable performer in its own tier. But that tier is well below the PG506-232. The PG506-232's nearest rivals include the A100 PCIe 80 GB and the L20, both of which are newer or higher-end parts. The PG506-232 holds its own against them, beating the A100 by 8.7% and only losing to the L20 by 10.4%.

For users whose workloads align with the Geekbench OpenCL test, the PG506-232 is the clear choice. For users who require maximum memory capacity or who believe the V100's higher theoretical compute throughput will matter in their specific applications, the V100 SXM2 32 GB remains a defensible pick — but the benchmark evidence in this database does not support that choice. The PG506-232 wins the head-to-head, and the verdict follows the data.

Head-to-Head Benchmarks

The only head-to-head benchmark available is Geekbench OpenCL. In this test, the PG506-232 scores 225,124, while the V100 SXM2 32 GB scores 131,696. The PG506-232 wins by 70.9%. This is a massive delta, and it is worth contextualizing against the rivals listed for each card.

The PG506-232's 225,124 OpenCL score is 8.7% higher than the NVIDIA A100 PCIe 80 GB's average of 207,124, and 2.4% higher than the AMD Radeon PRO W7900D's 219,827. It is 14.9% higher than the RTX 6000D's 195,964. The only rival that beats it is the NVIDIA L20 at 251,147, a 10.4% edge. The PG506-232, despite being an older end-of-life part, sits right at the top of its peer group.

The V100 SXM2 32 GB's OpenCL score of 131,696 is actually its weaker result; its Vulkan score is 143,765, which is 9.2% higher. But even the stronger Vulkan score would not close the gap to the PG506-232. The V100's average of 137,731 puts it within 1.4% of all four of its nearest rivals — the V100 PCIe 16 GB (138,063), the Instinct MI100 (139,035), the Radeon PRO V620 (136,472), and the Radeon Pro W6800X Duo (135,774). This tight clustering indicates the V100 SXM2 32 GB is a consistent mid-tier performer. The PG506-232, by contrast, operates in a higher league entirely.

The 70.9% delta in the head-to-head is the single most important number in this comparison. It dwarfs every other differential in the data. The PG506-232's advantage over its nearest rival (8.7% vs A100) is less than one-eighth of its advantage over the V100. The V100's advantage over its nearest rival (1.4% vs W6800X Duo) is negligible by comparison. The conclusion is straightforward: in the benchmark that matters most for this comparison, the PG506-232 is categorically faster.

FAQ

Q: Which GPU has the higher Geekbench OpenCL score?

A: The NVIDIA PG506-232 scores 225,124, while the NVIDIA Tesla V100 SXM2 32 GB scores 131,696. The PG506-232 wins by 70.9%.

Q: Does the Tesla V100 SXM2 32 GB win any benchmark in the head-to-head comparison?

A: No. The only head-to-head benchmark listed is Geekbench OpenCL, and the PG506-232 wins that one. The V100 has zero wins in the head-to-head data.

Q: How does the PG506-232 compare to the NVIDIA A100 PCIe 80 GB?

A: The PG506-232 scores 225,124, which is 8.7% higher than the A100 PCIe 80 GB's average score of 207,124.

Q: What is the closest rival to the Tesla V100 SXM2 32 GB?

A: The NVIDIA Tesla V100 PCIe 16 GB is the closest, with an average score of 138,063, which is 0.2% higher than the SXM2's 137,731 average.

Q: Does the V100 SXM2 32 GB have more memory than the PG506-232?

A: Yes. The V100 SXM2 32 GB has 32 GB of HBM2 memory, while the PG506-232 has 24 GB of HBM2. The V100 also has a wider 4096-bit memory bus versus 3072-bit.

Q: Which GPU has the higher FP32 compute throughput?

A: The V100 SXM2 32 GB is rated at 15.67 TFLOPS FP32, while the PG506-232 is rated at 10.32 TFLOPS. The V100 also has a 2:1 FP16 ratio (31.33 TFLOPS) versus the PG506-232's 1:1 ratio (10.32 TFLOPS).

Architecture Differences

The two GPUs come from different NVIDIA architectures, and the gap in their benchmark performance reflects a generational shift. The PG506-232 is built on the Ampere architecture, using the GA100 chip. The V100 SXM2 32 GB is a Volta-generation part, built on the GV100 chip. The PG506-232 belongs to the "Server Ampere (Axx)" generation, while the V100 is from the "Tesla Volta (Vxx)" generation.

The manufacturing process differs significantly. The PG506-232 uses a 7 nm process at TSMC, while the V100 uses a 12 nm process at the same foundry. The PG506-232 packs 54,200 million transistors onto an 826 mm² die, yielding a transistor density of 65.6 million per mm². The V100 has 21,100 million transistors on a similar 815 mm² die, but with a much lower density of 25.9 million per mm². The PG506-232 crams more than 2.5 times as many transistors into roughly the same physical space.

The memory subsystems differ as well. Both use HBM2, but the PG506-232 has a 3072-bit bus and 933.1 GB/s bandwidth, while the V100 has a wider 4096-bit bus but slightly lower bandwidth at 898.0 GB/s. The V100 compensates with more capacity: 32 GB versus 24 GB. Clock speeds also differ — the PG506-232 runs at 930 MHz base and 1440 MHz boost, while the V100 runs higher at 1290 MHz base and 1530 MHz boost. Memory clocks differ too: the PG506-232 runs at 1215 MHz (2.4 Gbps effective), while the V100 runs at 877 MHz (1754 Mbps effective).

The compute resources tell a story of trade-offs. The V100 has more shading units (5120 vs 3584), more TMUs (320 vs 224), more ROPs (128 vs 96), and far more tensor cores (640 vs 224). Its theoretical pixel rate is 195.8 GPixel/s versus 138.2 GPixel/s, and its texture rate is 489.6 GTexel/s versus 322.6 GTexel/s. Despite all this, the PG506-232 dominates in the actual benchmark. This suggests the Ampere architecture's efficiency and memory bandwidth advantages (933.1 GB/s vs 898.0 GB/s) outweigh the V100's raw resource counts in this workload.

Specification Differences

The two cards differ across nearly every measurable specification. The PG506-232 is a dual-slot card measuring 267 mm in length and 112 mm in height, with an 8-pin EPS power connector and a suggested PSU of 450 W. Its TDP is 165 W. The V100 SXM2 32 GB is an SXM module with no length or height listed, no power connector (power is supplied through the module interface), and a suggested PSU of 600 W. Its TDP is 250 W.

The bus interfaces differ: the PG506-232 uses PCIe 4.0 x16, while the V100 uses PCIe 3.0 x16. Neither card has display outputs. The PG506-232 has no listed APIs for DirectX, OpenGL, or Vulkan, while the V100 supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4.

Release dates and product lineage differ as well. The PG506-232 was released on 2021-04-11, succeeding the Tesla Turing generation and preceding Server Ada. The V100 SXM2 32 GB was released on 2018-03-26, succeeding Tesla Pascal and preceding Tesla Turing. Both are end-of-life products. Neither has a launch MSRP listed.

The memory configurations are a key differentiator. The PG506-232 has 24 GB of HBM2 on a 3072-bit bus with 933.1 GB/s bandwidth. The V100 has 32 GB of HBM2 on a 4096-bit bus with 898.0 GB/s bandwidth. The V100 has more capacity and a wider bus, but the PG506-232 has higher effective bandwidth. The V100's memory clock is 877 MHz (1754 Mbps effective), while the PG506-232's is 1215 MHz (2.4 Gbps effective).

The shading and compute specifications also differ markedly. The PG506-232 has 3584 shading units, 224 TMUs, 96 ROPs, and 224 tensor cores. The V100 has 5120 shading units, 320 TMUs, 128 ROPs, and 640 tensor cores. The V100's FP32 throughput is 15.67 TFLOPS versus 10.32 TFLOPS, and its FP16 throughput is 31.33 TFLOPS (2:1) versus 10.32 TFLOPS (1:1). The PG506-232's pixel rate is 138.2 GPixel/s and texture rate is 322.6 GTexel/s, while the V100's are 195.8 GPixel/s and 489.6 GTexel/s respectively. In every raw compute specification, the V100 leads — yet the PG506-232 wins the benchmark. The data overrides the spec sheet.