NVIDIA PG506-232 vs NVIDIA Tesla P100 PCIe 12 GB Comparison

The NVIDIA PG506-232 is, by the recorded data, in a different performance class than the Tesla P100 PCIe 12 GB. In the one head-to-head benchmark logged in the database, Geekbench OpenCL, the PG506-232 scores 225124 against 79396, a gap of 183.5 percent. Both cards are end-of-life server accelerators from NVIDIA, but they represent two different eras: the PG506-232 is an Ampere-generation GA100 part on a 7 nm process, while the Tesla P100 PCIe 12 GB is a Pascal-generation GP100 part on a 16 nm process. The data points to a clear recommendation: any workload where GPU throughput matters favors the PG506-232, and the only argument for the P100 is its DirectX 12, OpenGL 4.6, and Vulkan 1.3 API support, which the PG506-232 lacks entirely.

The Verdict

Pick the NVIDIA PG506-232 for compute. Its Geekbench OpenCL score of 225124 sits in the 99th percentile of all GPUs in the database, while the Tesla P100 PCIe 12 GB's 79396 places it in the 92nd percentile. The head-to-head margin of 183.5 percent is not a close race; it is a generational blowout driven by newer silicon, more memory, and Tensor Core hardware the P100 does not have.

The Tesla P100 PCIe 12 GB still has two defensible niches. First, it is the only one of the pair with documented graphics API support: DirectX 12 (feature level 12_1), OpenGL 4.6, and Vulkan 1.3. The PG506-232 has no listed DirectX, OpenGL, or Vulkan support and no display outputs, marking it as a pure compute card. Second, workloads that specifically exploit its 2:1 FP16 ratio, where half-precision runs at 19.05 TFLOPS versus 9.526 TFLOPS FP32, can extract more from the P100 than its FP32 figure suggests. That said, the PG506-232 counters with 224 Tensor Cores, so dedicated mixed-precision workloads favor the newer card as well.

Both are dual-slot, headless accelerators with the same 267 mm (10.5 inches) board length and no display outputs. Neither is still in production.

FAQ

Q: How much faster is the PG506-232 than the Tesla P100 PCIe 12 GB?

A: In the database's Geekbench OpenCL test, the PG506-232 scores 225124 versus 79396 for the P100, a 183.5 percent advantage for the PG506-232.

Q: How do the two cards rank against all GPUs in the database?

A: The PG506-232 sits in the 99th percentile of all recorded GPUs. The Tesla P100 PCIe 12 GB sits in the 92nd percentile.

Q: Which card has more memory bandwidth?

A: The PG506-232, with 933.1 GB/s of HBM2 bandwidth versus 549.1 GB/s for the P100. Both use a 3072-bit HBM2 bus, so the bandwidth gap comes from faster memory: 2.4 Gbps effective on the PG506-232 against 1430 Mbps effective on the P100.

Q: Do either of these cards support gaming or display output?

A: Neither has display outputs. However, the Tesla P100 lists DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.3 support, while the PG506-232 lists none of these APIs.

Q: Which card uses less power?

A: The PG506-232, with a TDP of 165 W versus 250 W for the P100. The suggested PSU ratings also differ: 450 W for the PG506-232 and 600 W for the P100.

Q: How does the PG506-232 compare to its own rivals?

A: Among its nearest rivals, the PG506-232 leads the AMD Radeon PRO W7900D by 2.4 percent, the NVIDIA A100 PCIe 80 GB by 8.7 percent, and the NVIDIA RTX 6000D by 14.9 percent, while trailing the NVIDIA L20 by 10.4 percent.

Architecture Differences

The PG506-232 is built on the GA100 chip, NVIDIA's Ampere architecture, and belongs to the Server Ampere (Axx) generation. It is fabricated by TSMC on a 7 nm process, packs 54,200 million transistors onto an 826 mm² die, and reaches a transistor density of 65.6M per mm². Its lineage runs from Tesla Turing to Server Ada.

The Tesla P100 PCIe 12 GB uses the GP100 chip, Pascal architecture, and the Tesla Pascal (Pxx) generation. Also made by TSMC, it uses a 16 nm process with 15,300 million transistors on a 610 mm² die, yielding 25.1M transistors per mm². Its predecessor was Tesla Maxwell and its successor was Tesla Volta.

The architectural consequences are visible throughout the data. Ampere delivers roughly two and a half times the transistor count on a die only moderately larger, and density more than doubles from 25.1M to 65.6M per mm². Critically, the PG506-232 carries 224 Tensor Cores; the P100 has none, since Tensor Cores arrived after Pascal in this product line. Boost clock actually favors the P100's era-typical approach in base terms (1190 MHz base versus 930 MHz), but the PG506-232 boosts higher at 1440 MHz versus 1329 MHz.

Specification Differences

• Memory size: 24 GB (PG506-232) versus 12 GB (Tesla P100 PCIe 12 GB), both HBM2 on a 3072-bit bus.
• Memory bandwidth: 933.1 GB/s versus 549.1 GB/s.
• Process node: 7 nm versus 16 nm, both TSMC.
• Transistors and die: 54,200 million on 826 mm² versus 15,300 million on 610 mm².
• TDP: 165 W versus 250 W.
• Suggested PSU: 450 W versus 600 W.
• Power connectors: 8-pin EPS versus 1x 8-pin.
• Bus interface: PCIe 4.0 x16 versus PCIe 3.0 x16.
• Tensor Cores: 224 versus none.
• FP32 performance: 10.32 TFLOPS versus 9.526 TFLOPS.
• FP16 behavior: 10.32 TFLOPS at 1:1 versus 19.05 TFLOPS at 2:1.
• Boost clock: 1440 MHz versus 1329 MHz; base clock 930 MHz versus 1190 MHz.
• Pixel rate: 138.2 GPixel/s versus 127.6 GPixel/s.
• Texture rate: 322.6 GTexel/s versus 297.7 GTexel/s.
• APIs: none listed on the PG506-232 versus DirectX 12 (12_1), OpenGL 4.6, Vulkan 1.3 on the P100.
• Height spec: 112 mm recorded for the PG506-232, not recorded for the P100; length is identical at 267 mm.
• Release date: 2021-04-11 for the PG506-232 versus 2016-06-19 for the P100. The P100's launch MSRP was 4,599 USD.

Interestingly, the raw shader resources are identical on paper: 3584 shading units, 224 TMUs, and 96 ROPs on both cards. Neither has RT cores. The difference is in efficiency and throughput per resource, plus the PG506-232's Tensor Cores and doubled memory capacity.

Head-to-Head Benchmarks

The database contains one direct comparison, and it is decisive.

In Geekbench OpenCL, the PG506-232 scores 225124 and the Tesla P100 PCIe 12 GB scores 79396. The winner is the PG506-232 by 183.5 percent. In practical terms, the PG506-232 delivers close to three times the P100's measured throughput in this compute test, despite drawing 85 W less power according to the listed TDPs.

Context from each card's rival set sharpens the picture. The P100's 79396 average score lands it within a tight cluster: the Tesla P100 PCIe 16 GB averages 79605 (0.3 percent ahead of it), the GeForce RTX 5090 averages 79842 (0.6 percent ahead), the Radeon RX 6850M XT averages 78940 (0.6 percent behind), and the Radeon Pro Vega 64X averages 80959 (1.9 percent ahead). The P100 is in a crowded midfield where siblings and mobile parts trade blows.

The PG506-232's 225124 average, by contrast, places it above the AMD Radeon PRO W7900D at 219827 (+2.4 percent), the NVIDIA A100 PCIe 80 GB at 207124 (+8.7 percent), and the NVIDIA RTX 6000D at 195964 (+14.9 percent). Only the NVIDIA L20 at 251147 sits above it, by 10.4 percent. Beating the A100 PCIe 80 GB by 8.7 percent despite that card's larger memory pool is a notable result for the PG506-232.

Where Each One Wins

PG506-232 wins:

• General GPU compute. A 183.5 percent Geekbench OpenCL advantage over the P100 is the headline number, supported by higher FP32 throughput (10.32 versus 9.526 TFLOPS) and far higher memory bandwidth (933.1 versus 549.1 GB/s).
• Large-dataset workloads. 24 GB of HBM2 doubles the P100's 12 GB capacity, and the 3072-bit bus is paired with faster 2.4 Gbps effective memory.
• Mixed-precision and AI inference. The 224 Tensor Cores give it dedicated hardware the P100 simply lacks.
• Power- and platform-constrained deployments. A 165 W TDP, a 450 W suggested PSU, and PCIe 4.0 x16 make it easier to host and faster to feed with data than the 250 W, PCIe 3.0-based P100.
• Headless server racks where maximum throughput per slot matters; it outperforms the A100 PCIe 80 GB, RTX 6000D, and Radeon PRO W7900D in the recorded averages.

Tesla P100 PCIe 12 GB wins:

• API compatibility. It is the only card of the pair with DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.3 support, so any workload tied to those APIs has exactly one option here.
• FP32-to-FP16 ratio exploitation. Its 2:1 half-precision rate of 19.05 TFLOPS nearly doubles its FP32 figure, whereas the PG506-232 runs FP16 at a 1:1 ratio of 10.32 TFLOPS. Pure FP16 shader work without Tensor Core usage is a rare scenario where the P100's paper throughput exceeds the PG506-232's.
• Legacy platform compatibility. PCIe 3.0 x16 means it drops into older host systems without the PCIe 4.0 requirement implied by the newer card's interface.

The overall record in the database is one win for the PG506-232 and zero for the P100, and that ratio reflects reality: unless API support or the FP16 ratio is the deciding factor, the Ampere card is the clear choice.