NVIDIA CMP 40HX vs NVIDIA Quadro GP100 Comparison

The NVIDIA Quadro GP100 and the NVIDIA CMP 40HX represent two distinct design philosophies from the same manufacturer, separated by nearly five years of architectural evolution. The data places both in the 93rd percentile of all GPUs, indicating they are both high-performance parts, yet their benchmark results and specifications reveal fundamentally different strengths. This analysis breaks down the data to show where each card stands.

Head-to-Head Benchmarks

The only direct benchmark comparison available is the Geekbench OpenCL test. In this test, the CMP 40HX posts a score of 93,395, while the Quadro GP100 scores 87,445. This gives the CMP 40HX a 6.4% lead over the GP100. This is a significant margin in a compute-focused API like OpenCL, suggesting the newer Turing architecture handles general compute workloads more efficiently than the older Pascal design.

Looking at the broader context through the nearest rivals data, the picture becomes more nuanced. The Quadro GP100’s average score of 87,445 is only 0.4% behind the AMD Radeon PRO W7600, which scores 87,108. It sits 4% behind the NVIDIA RTX A4500 (91,671) and 4.6% behind the RTX A4500 Mobile (91,134). The CMP 40HX, with its higher OpenCL score, is 1.7% ahead of the Radeon PRO W7600 and 4.4% ahead of the AMD Radeon PRO W6600. However, its average benchmark score is listed as 85,637, which is lower than the GP100’s 87,445. This discrepancy is explained by the CMP 40HX having two benchmark entries: its OpenCL score of 93,395 and a separate Vulkan score of 77,879. The average pulls the CMP 40HX down, while the GP100 only has the single OpenCL score.

In the direct head-to-head, the CMP 40HX is the clear winner in OpenCL. A 6.4% advantage is substantial, and it indicates that the Turing architecture’s newer instruction set and feature set provide a real performance edge in this specific workload. The GP100’s much larger memory bus and HBM2 memory do not translate into a win here, as the benchmark likely favors raw shading throughput and architectural efficiency over memory bandwidth. The data shows a single, decisive victory for the CMP 40HX in the available comparison, but the overall average scores suggest the GP100 is also a very capable competitor when considering its consistent performance across the board.

FAQ

Q: Which GPU has the higher Geekbench OpenCL score?

A: The NVIDIA CMP 40HX scores 93,395, which is 6.4% higher than the Quadro GP100’s score of 87,445.

Q: How do the average benchmark scores compare between the two cards?

A: The Quadro GP100 has an average benchmark score of 87,445, while the CMP 40HX has an average of 85,637. This makes the GP100 2.1% higher than the CMP 40HX, despite losing the single OpenCL head-to-head test.

Q: What is the difference in their memory configurations?

A: The Quadro GP100 has 16 GB of HBM2 memory on a 4096-bit bus, providing 732.2 GB/s of bandwidth. The CMP 40HX has 8 GB of GDDR6 memory on a 256-bit bus, providing 448.0 GB/s of bandwidth.

Q: Which GPU has more shading units?

A: The Quadro GP100 has 3,584 shading units, while the CMP 40HX has 2,304. The GP100 also has more texture mapping units (224 vs. 144) and more ROPs (96 vs. 64).

Q: Are there any differences in their API support?

A: Yes. The CMP 40HX supports DirectX 12 Ultimate (12_2) and Vulkan 1.4, while the Quadro GP100 supports DirectX 12 (12_1) and Vulkan 1.3. Both support OpenGL 4.6.

Q: What is the TDP and power connector requirement for each?

A: The Quadro GP100 has a TDP of 235 W and requires a 550 W power supply. The CMP 40HX has a lower TDP of 185 W and requires a 450 W power supply. Both use a single 8-pin power connector.

Architecture Differences

The two cards are built on different architectures from different eras. The Quadro GP100 uses the GP100 chip, based on the Pascal architecture, manufactured on a 16 nm process at TSMC. This is a massive chip, with 15,300 million transistors on a 610 mm² die, giving it a transistor density of 25.1M per mm². The CMP 40HX, in contrast, uses the TU106 chip, based on the newer Turing architecture, built on a 12 nm process at the same foundry. This chip is smaller, with 10,800 million transistors on a 445 mm² die, resulting in a slightly lower transistor density of 24.3M per mm². The Pascal chip is physically larger and has more transistors, but the Turing chip is crafted on a more advanced process node.

The most significant architectural difference lies in the feature set. The CMP 40HX’s Turing architecture includes 36 RT cores and 288 tensor cores, which are entirely absent from the Pascal-based Quadro GP100. This means the CMP 40HX has dedicated hardware for ray tracing and AI-accelerated tasks, while the GP100 must rely on its general-purpose shaders for these workloads. The API support reflects this, with the CMP 40HX supporting DirectX 12 Ultimate (12_2) and Vulkan 1.4, whereas the GP100 is limited to DirectX 12 (12_1) and Vulkan 1.3. The GP100, however, compensates with sheer compute scale, offering 3,584 shading units, 224 TMUs, and 96 ROPs, compared to the CMP 40HX’s 2,304 shading units, 144 TMUs, and 64 ROPs. This gives the GP100 higher theoretical pixel and texture rates, at 138.5 GPixel/s and 323.2 GTexel/s, respectively, versus 105.6 GPixel/s and 237.6 GTexel/s for the CMP 40HX.

Specification Differences

The specifications where these two cards differ are substantial. The Quadro GP100 has a base clock of 1304 MHz and a boost clock of 1443 MHz, while the CMP 40HX runs faster at 1470 MHz base and 1650 MHz boost. Memory is a major differentiator: the GP100 has 16 GB of HBM2 on a 4096-bit bus with 732.2 GB/s bandwidth, while the CMP 40HX has 8 GB of GDDR6 on a 256-bit bus with 448.0 GB/s bandwidth. The compute capabilities differ as well, with the GP100 delivering 10.34 TFLOPS of FP32 and 20.69 TFLOPS of FP16, while the CMP 40HX delivers 7.603 TFLOPS of FP32 and 15.21 TFLOPS of FP16. The GP100 has a higher TDP of 235 W and requires a 550 W power supply, while the CMP 40HX has a lower TDP of 185 W and a 450 W power supply suggestion.

The physical and interface specifications also diverge. The GP100 is longer at 267 mm (10.5 inches), while the CMP 40HX is 229 mm (9 inches) long; both have a height of 111 mm. The GP100 uses a PCIe 3.0 x16 interface, while the CMP 40HX uses a PCIe 1.0 x4 interface. Most tellingly, the GP100 has display outputs (1x DVI and 4x DisplayPort 1.4a), whereas the CMP 40HX has no display outputs at all, reflecting its purpose as a mining card. The CMP 40HX has a launch MSRP of 699 USD, while the GP100 has no launch MSRP listed. The GP100 was released on 2016-09-30, while the CMP 40HX was released on 2021-02-24.

Where Each One Wins

The NVIDIA Quadro GP100 wins in scenarios that demand raw memory bandwidth and large memory capacity. Its 16 GB of HBM2 with 732.2 GB/s bandwidth is more than double the bandwidth of the CMP 40HX. This makes it better suited for workloads that are heavily memory-bound, such as large dataset processing, scientific simulations, or high-resolution rendering where the entire dataset must reside in VRAM. Its higher FP32 throughput of 10.34 TFLOPS also gives it an edge in traditional compute tasks that don’t leverage the Turing-specific features. Furthermore, the GP100 has display outputs, making it usable in a traditional workstation environment where a visual output is required.

The NVIDIA CMP 40HX wins in the direct OpenCL benchmark, showing a 6.4% advantage. This suggests it is more efficient at executing general-purpose compute workloads despite having fewer shading units. Its Turing architecture brings dedicated RT cores and tensor cores, which are essential for ray-traced rendering and AI inference tasks, respectively. These features give it a functional advantage in modern workloads that can utilize them, even if the raw FP32 numbers are lower. Its lower TDP of 185 W and smaller physical footprint make it easier to integrate into dense compute systems, and its support for DirectX 12 Ultimate and Vulkan 1.4 ensures compatibility with the latest graphics APIs.

The Verdict

The data paints a clear picture of two specialized tools. The NVIDIA Quadro GP100 is a professional workstation card from the Pascal era, prioritizing massive memory bandwidth and capacity. Its higher average benchmark score of 87,445 versus 85,637 for the CMP 40HX, and its 16 GB of HBM2 memory, make it the choice for professionals whose work involves huge datasets that need to be held in VRAM. Its higher FP32 throughput and display outputs reinforce its role as a traditional compute and visualization workhorse.

The NVIDIA CMP 40HX is a mining-focused card from the Turing era that happens to be a strong general compute performer. Its victory in the Geekbench OpenCL test by 6.4% shows that its architectural efficiency can outperform the older, larger GP100 in certain tasks. The inclusion of RT and tensor cores makes it a more future-proof option for workloads that leverage these features. However, its lack of display outputs and smaller 8 GB memory pool limit its use case to headless compute environments.

Ultimately, the choice depends on the workload. For memory-intensive professional tasks requiring a display, the Quadro GP100 is the data-backed selection. For pure compute performance in a headless server environment, particularly with modern APIs or tensor/RT workloads, the CMP 40HX’s benchmark victory makes it the stronger candidate. The GP100 leads in average score, but the CMP 40HX leads in the direct head-to-head test, and that single win is the most direct comparison available.