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

The NVIDIA PG506-232 and the NVIDIA Tesla V100 PCIe 32 GB are both end-of-life server accelerators, but they represent distinct generations of NVIDIA’s compute lineup. The benchmark data clearly separates them: the PG506-232 is the faster card in raw compute tests, while the V100 offers a larger memory pool and a different architecture. The PG506-232 scores 225,124 in Geekbench OpenCL, which is 33.4% higher than the V100’s 168,763. However, the V100 counters with 32 GB of HBM2 memory versus the PG506-232’s 24 GB, and it retains a higher shading unit count. The choice between them depends entirely on whether the workload prioritizes raw compute throughput or larger memory capacity for models that exceed the PG506-232’s 24 GB frame buffer.

The Verdict

The data points to a clear split in use cases. For compute-bound tasks where memory capacity is not the limiting factor, the NVIDIA PG506-232 is the superior choice. Its Geekbench OpenCL score of 225,124 places it in the 99th percentile of all GPUs, and it outperforms the V100 by 33.4% in the single head-to-head benchmark available. The PG506-232 also sits 8.7% ahead of the NVIDIA A100 PCIe 80 GB in average score, showing it is a high-tier performer within its own generation.

Conversely, the NVIDIA Tesla V100 PCIe 32 GB is the pick for workloads that need more than 24 GB of memory. Its 32 GB HBM2 frame buffer is 33% larger than the PG506-232’s, which is crucial for very large deep learning models or datasets that cannot be sharded. The V100’s average benchmark score of 150,305 places it in the 96th percentile, and while it trails the PG506-232, it remains competitive with newer cards like the NVIDIA A10G, which scores 151,963 (a -1.1% delta for the V100). However, the V100’s 12 nm process and older Volta architecture mean it consumes 250 W versus the PG506-232’s 165 W, making the newer card more power-efficient per unit of compute.

The verdict is straightforward: choose the PG506-232 for pure speed and efficiency. Choose the V100 for its 32 GB memory capacity, accepting a 33.4% compute deficit in OpenCL workloads. There is no tie-breaker in the data; the wins tally is 1-0 in favor of the PG506-232.

Architecture Differences

The two cards are built on fundamentally different architectures and process nodes. The PG506-232 uses the GA100 chip on the Ampere architecture, fabricated on TSMC’s 7 nm process. This chip packs 54,200 million transistors into an 826 mm² die, yielding a transistor density of 65.6 million per square millimeter. In contrast, the V100 uses the GV100 chip on the older Volta architecture, built on TSMC’s 12 nm process. The GV100 contains 21,100 million transistors on an 815 mm² die, giving a density of just 25.9 million per square millimeter. The PG506-232’s transistor density is more than 2.5 times higher, reflecting the process node advantage.

The memory subsystems differ significantly in configuration, though bandwidth is comparable. The PG506-232 has a 3072-bit memory bus with 24 GB of HBM2, achieving 933.1 GB/s of bandwidth. The V100 has a wider 4096-bit bus with 32 GB of HBM2, but its bandwidth is slightly lower at 897.0 GB/s. The PG506-232’s memory clock is listed as 1215 MHz (2.4 Gbps effective), while the V100’s memory runs at 876 MHz (1752 Mbps effective). Despite the V100’s wider bus, the PG506-232 edges out slightly on bandwidth.

Compute resources are distributed differently as well. The V100 has 5120 shading units, 320 texture mapping units (TMUs), and 128 raster operation pipelines (ROPs), along with 640 tensor cores. The PG506-232 has fewer shading units at 3584, fewer TMUs at 224, and fewer ROPs at 96, but it includes 224 tensor cores. The V100’s higher shading unit count does not translate to a win in the OpenCL benchmark, which is a key observation. The PG506-232 also has a higher boost clock at 1440 MHz versus the V100’s 1380 MHz, though the V100 has a higher base clock at 1230 MHz versus 930 MHz.

Feature support differs on the API front. The V100 lists DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4 support. The PG506-232 lists no API support in the data pack, which is typical for a compute-focused accelerator with no display outputs. Power delivery also diverges: the PG506-232 uses a single 8-pin EPS connector with a 165 W TDP and a suggested 450 W PSU, while the V100 uses two 8-pin connectors with a 250 W TDP and a suggested 600 W PSU.

Head-to-Head Benchmarks

The only head-to-head benchmark available is Geekbench OpenCL, and it is a decisive win for the PG506-232. The PG506-232 scores 225,124, while the V100 scores 168,763, yielding a delta of 33.4% in favor of the Ampere card. This is a substantial margin that reflects the generational leap in compute efficiency.

Contextualizing this score against their respective nearest rivals adds depth. The PG506-232’s 225,124 average is 8.7% higher than the NVIDIA A100 PCIe 80 GB’s 207,124, and it is 14.9% ahead of the NVIDIA RTX 6000D’s 195,964. It trails the NVIDIA L20’s 251,147 by 10.4%, but it beats the AMD Radeon PRO W7900D’s 219,827 by 2.4%. This places the PG506-232 as a strong mid-to-high tier performer in the OpenCL compute space.

The V100’s 168,763 OpenCL score is closer to its rivals. It sits only 1.1% behind the NVIDIA A10G’s 151,963, and it is 6.5% behind the AMD Radeon Pro W6800X’s 160,671. It outperforms the AMD Instinct MI100’s 139,035 by 8.1%, but it falls 7.5% short of the NVIDIA A100 PCIe 40 GB’s 162,504. The 33.4% gap between the PG506-232 and the V100 is far larger than any delta these cards show against their immediate competitors, underscoring the architectural gulf between Ampere and Volta.

There is no Geekbench Vulkan result for the PG506-232 in the data, but the V100 posts a Vulkan score of 131,847, which is lower than its OpenCL score. This suggests the V100 performs better in OpenCL workloads, but without a comparable PG506-232 result, no direct cross-architecture Vulkan comparison is possible.

Specification Differences

The two cards differ on nearly every key specification, and the table below highlights the fields where they diverge.

| Specification | NVIDIA PG506-232 | NVIDIA Tesla V100 PCIe 32 GB |

|---|---|---|

| Chip | GA100 | GV100 |

| Architecture | Ampere | Volta |

| Generation | Server Ampere (Axx) | Tesla Volta (Vxx) |

| Process Node | 7 nm | 12 nm |

| Transistors | 54,200 million | 21,100 million |

| Die Size | 826 mm² | 815 mm² |

| Transistor Density | 65.6M / mm² | 25.9M / mm² |

| Base Clock | 930 MHz | 1230 MHz |

| Boost Clock | 1440 MHz | 1380 MHz |

| Memory Clock | 1215 MHz (2.4 Gbps effective) | 876 MHz (1752 Mbps effective) |

| Memory Size | 24 GB | 32 GB |

| Memory Bus Width | 3072 bit | 4096 bit |

| Memory Bandwidth | 933.1 GB/s | 897.0 GB/s |

| Shading Units | 3584 | 5120 |

| TMUs | 224 | 320 |

| ROPs | 96 | 128 |

| Tensor Cores | 224 | 640 |

| Pixel Rate | 138.2 GPixel/s | 176.6 GPixel/s |

| Texture Rate | 322.6 GTexel/s | 441.6 GTexel/s |

| FP32 | 10.32 TFLOPS | 14.13 TFLOPS |

| FP16 | 10.32 TFLOPS (1:1) | 28.26 TFLOPS (2:1) |

| TDP | 165 W | 250 W |

| Power Connectors | 8-pin EPS | 2x 8-pin |

| Suggested PSU | 450 W | 600 W |

| Bus Interface | PCIe 4.0 x16 | PCIe 3.0 x16 |

| APIS | None listed | DirectX 12 (12_1), OpenGL 4.6, Vulkan 1.4 |

| Dimensions | 267 mm (10.5 inches) length, 112 mm (4.4 inches) height | Not specified |

| Release Date | 2021-04-11 | 2018-03-26 |

| Predecessor | Tesla Turing | Tesla Pascal |

| Successor | Server Ada | Tesla Turing |

| Percentile | 99th | 96th |

| Avg Benchmark Score | 225,124 | 150,305 |

The release dates confirm the generational gap: the PG506-232 launched in April 2021, while the V100 launched in March 2018. The PG506-232 also uses PCIe 4.0 x16, while the V100 is limited to PCIe 3.0 x16, doubling the theoretical interconnect bandwidth for the newer card.

FAQ

Q: Which card is faster in OpenCL benchmarks?

A: The NVIDIA PG506-232 is significantly faster. It scores 225,124 in Geekbench OpenCL, which is 33.4% higher than the Tesla V100’s 168,763.

Q: Does the Tesla V100 have more memory?

A: Yes. The V100 features 32 GB of HBM2 memory, while the PG506-232 has 24 GB. The V100 also has a wider 4096-bit memory bus, though its bandwidth of 897.0 GB/s is slightly lower than the PG506-232’s 933.1 GB/s.

Q: What are the power consumption differences?

A: The PG506-232 has a 165 W TDP with a single 8-pin EPS connector and a suggested 450 W PSU. The V100 has a 250 W TDP with two 8-pin connectors and a suggested 600 W PSU.

Q: How do these cards compare to their nearest rivals?

A: The PG506-232 is 8.7% ahead of the NVIDIA A100 PCIe 80 GB and 14.9% ahead of the NVIDIA RTX 6000D, but 10.4% behind the NVIDIA L20. The V100 is 1.1% behind the NVIDIA A10G, 6.5% behind the AMD Radeon Pro W6800X, and 7.5% behind the NVIDIA A100 PCIe 40 GB.

Q: Which card has more shading units and tensor cores?

A: The V100 has more of both. It has 5120 shading units and 640 tensor cores, whereas the PG506-232 has 3584 shading units and 224 tensor cores.

Q: Are there any API differences?

A: Yes. The V100 supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. The PG506-232 lists no API support, reflecting its compute-only design with no display outputs.