NVIDIA CMP 40HX vs NVIDIA Tesla P100 PCIe 12 GB Comparison

The NVIDIA CMP 40HX and the NVIDIA Tesla P100 PCIe 12 GB represent two very different approaches to GPU computing, separated by a generation of architecture and designed for entirely distinct workloads. The data shows a clear split: the CMP 40HX, a Turing-era mining card, dominates the single available compute benchmark, while the Tesla P100, a Pascal-era datacenter card, offers a larger memory pool and a wider interface. The benchmark results indicate that for raw compute throughput in the tested workload, the newer architecture wins decisively, but the older card still holds advantages in capacity and bandwidth that matter for specific tasks.

Where Each One Wins

The performance landscape is defined by the single head-to-head benchmark available: Geekbench OpenCL. In this test, the NVIDIA CMP 40HX scores 93,395, while the NVIDIA Tesla P100 PCIe 12 GB scores 79,396. That is a 17.6% delta in favor of the CMP 40HX, making it the clear winner in raw compute performance as measured by this workload. The CMP 40HX also holds a higher percentile rank among all GPUs at 93, compared to the Tesla P100's 92, though that gap is narrow.

Where the Tesla P100 wins is in memory capacity and bandwidth. The P100 offers 12 GB of HBM2 memory on a 3072-bit bus, delivering 549.1 GB/s of bandwidth. The CMP 40HX, by contrast, has 8 GB of GDDR6 on a 256-bit bus, providing 448.0 GB/s. For workloads that are memory-bound rather than compute-bound, the P100's extra 4 GB and 101.1 GB/s of additional bandwidth could prove decisive, even if its raw compute score is lower. The data suggests a use-case split: the CMP 40HX for compute-heavy tasks that fit within its 8 GB frame buffer, and the Tesla P100 for larger datasets or memory-intensive operations where capacity and bandwidth take priority over raw FLOPs.

Architecture Differences

The architectural gap between these two cards is substantial. The CMP 40HX is built on the Turing architecture, using the TU106 chip fabricated on a 12 nm process at TSMC. It packs 10,800 million transistors on a 445 mm² die, resulting in a transistor density of 24.3M / mm². The Tesla P100 uses the older Pascal architecture, built on the GP100 chip at 16 nm, also from TSMC. It houses 15,300 million transistors on a much larger 610 mm² die, with a slightly higher density of 25.1M / mm².

The feature sets diverge sharply. The CMP 40HX includes 36 RT cores and 288 tensor cores, reflecting Turing's focus on ray tracing and AI acceleration. The Tesla P100 has neither, as Pascal predates those dedicated hardware units. The CMP 40HX also supports DirectX 12 Ultimate (12_2) and Vulkan 1.4, while the P100 is limited to DirectX 12 (12_1) and Vulkan 1.3. Both cards support OpenGL 4.6. The P100 comes from the Tesla Pascal (Pxx) generation, with a predecessor in Tesla Maxwell and a successor in Tesla Volta, while the CMP 40HX is part of the Mining GPUs generation with no listed predecessor or successor.

Clock speeds and compute rates also differ. The CMP 40HX runs at a base of 1470 MHz and a boost of 1650 MHz, while the P100 operates at 1190 MHz base and 1329 MHz boost. This clock advantage helps the CMP 40HX achieve 7.603 TFLOPS of FP32 performance, compared to the P100's 9.526 TFLOPS. Surprisingly, the P100 actually has higher raw FP32 throughput despite lower clocks, thanks to its larger shader count of 3584 versus the CMP 40HX's 2304. The CMP 40HX counters with 144 TMUs and 64 ROPs, while the P100 has 224 TMUs and 96 ROPs.

Head-to-Head Benchmarks

The only direct benchmark comparison available is Geekbench OpenCL, and it is a decisive victory for the CMP 40HX. The CMP 40HX scores 93,395 against the Tesla P100's 79,396, yielding a 17.6% delta. This is a meaningful margin that places the CMP 40HX well ahead of the P100 in this particular compute test. The CMP 40HX also demonstrates strength in Geekbench Vulkan, scoring 77,879, though no comparable Vulkan score is listed for the P100, so a direct comparison cannot be made there.

However, the P100's advantage lies in its memory subsystem. With 549.1 GB/s of bandwidth versus the CMP 40HX's 448.0 GB/s, the P100 moves data 22.6% faster. Its 12 GB capacity is 50% larger than the CMP 40HX's 8 GB. These differences are not reflected in the Geekbench OpenCL score, which may favor compute throughput over memory access patterns. The data implies that in workloads with large working sets or heavy data streaming, the P100 could outperform its newer rival despite the lower raw compute score.

The average benchmark scores reinforce the CMP 40HX's edge. The CMP 40HX has an average benchmark score of 85,637, while the P100 sits at 79,396. The CMP 40HX's nearest rivals include the AMD Radeon PRO W7600 at 87,108 (1.7% higher) and the NVIDIA Quadro GP100 at 87,445 (2.1% higher), showing it is competitive with a broad range of professional cards. The P100's nearest rivals include its own 16 GB variant at 79,605 (0.3% higher) and the GeForce RTX 5090 at 79,842 (0.6% higher), indicating the P100 sits in a slightly lower performance tier.

Specification Differences

The two cards diverge on nearly every specification. The CMP 40HX uses a 12 nm process node, while the P100 uses 16 nm. The CMP 40HX has 10,800 million transistors on a 445 mm² die, while the P100 has 15,300 million on a 610 mm² die. The CMP 40HX has a base clock of 1470 MHz and boost of 1650 MHz, versus the P100's 1190 MHz base and 1329 MHz boost. Memory differs completely: 8 GB GDDR6 on a 256-bit bus at 448.0 GB/s for the CMP 40HX, versus 12 GB HBM2 on a 3072-bit bus at 549.1 GB/s for the P100.

The compute units also differ. The CMP 40HX has 2304 shading units, 144 TMUs, and 64 ROPs, while the P100 has 3584 shading units, 224 TMUs, and 96 ROPs. The CMP 40HX includes 36 RT cores and 288 tensor cores; the P100 has none. Pixel rate favors the P100 at 127.6 GPixel/s versus 105.6 GPixel/s, as does texture rate at 297.7 GTexel/s versus 237.6 GTexel/s. FP32 performance favors the P100 at 9.526 TFLOPS versus 7.603 TFLOPS, and FP16 also favors the P100 at 19.05 TFLOPS versus 15.21 TFLOPS.

Power and interface specs differ as well. The CMP 40HX has a TDP of 185 W and a suggested PSU of 450 W, while the P100 draws 250 W and suggests a 600 W PSU. The CMP 40HX uses a PCIe 1.0 x4 interface, a curious limitation for a modern card, while the P100 uses PCIe 3.0 x16. Physical dimensions vary: the CMP 40HX is 229 mm long, 111 mm tall, and 35 mm wide, while the P100 is 267 mm long with no listed height or width. Both are dual-slot cards with a single 8-pin power connector and no display outputs. The CMP 40HX launched at 699 USD in February 2021, while the P100 launched at 4,599 USD in June 2016.

FAQ

Q: Which card performs better in the Geekbench OpenCL benchmark?

A: The NVIDIA CMP 40HX scores 93,395, which is 17.6% higher than the NVIDIA Tesla P100 PCIe 12 GB's score of 79,396.

Q: Does the Tesla P100 have any advantages over the CMP 40HX?

A: Yes, the P100 offers 12 GB of HBM2 memory with 549.1 GB/s of bandwidth, compared to the CMP 40HX's 8 GB of GDDR6 at 448.0 GB/s. It also has higher FP32 performance at 9.526 TFLOPS versus 7.603 TFLOPS.

Q: What architecture does each card use?

A: The CMP 40HX uses the Turing architecture on a 12 nm process, while the Tesla P100 uses the Pascal architecture on a 16 nm process.

Q: Does the CMP 40HX support ray tracing or AI acceleration?

A: Yes, the CMP 40HX includes 36 RT cores and 288 tensor cores. The Tesla P100 has neither of these hardware units.

Q: What is the difference in their bus interfaces?

A: The CMP 40HX uses a PCIe 1.0 x4 interface, while the Tesla P100 uses a PCIe 3.0 x16 interface. This is a significant difference in data transfer capability.

Q: How do their power requirements compare?

A: The CMP 40HX has a TDP of 185 W and a suggested PSU of 450 W, while the Tesla P100 has a TDP of 250 W and a suggested PSU of 600 W.

The Verdict

The data points to a clear choice for compute workloads as measured by Geekbench OpenCL: the NVIDIA CMP 40HX is the superior performer. Its 17.6% lead over the Tesla P100 in that benchmark, combined with a higher percentile rank of 93 versus 92, establishes it as the stronger card for raw compute throughput. The CMP 40HX also benefits from newer architecture features like RT cores and tensor cores, plus support for DirectX 12 Ultimate and Vulkan 1.4.

However, the Tesla P100 remains relevant for specific use cases. Its 12 GB memory capacity and 549.1 GB/s bandwidth are substantially larger than the CMP 40HX's 8 GB and 448.0 GB/s. For workloads that require holding large datasets in VRAM or that stress memory bandwidth, the P100's architecture could deliver better real-world performance despite lower compute scores. Its higher FP32 throughput of 9.526 TFLOPS versus 7.603 TFLOPS also indicates strength in traditional compute tasks that scale with shader count.

The CMP 40HX is the pick for users prioritizing compute speed, newer API support, and lower power draw (185 W versus 250 W). The Tesla P100 is the pick for users needing more memory capacity, higher bandwidth, and a proven datacenter pedigree, even if it comes with a higher power requirement and older architecture. The benchmark data cannot settle every debate, but for the single test available, the CMP 40HX wins decisively.