NVIDIA CMP 50HX vs NVIDIA Tesla P40 Comparison

Head-to-Head Benchmarks

The recorded data shows a clear and consistent winner across both benchmark tests. The NVIDIA Tesla P40 outperforms the NVIDIA CMP 50HX in every measured workload, though the margin varies significantly between the two APIs.

In the Geekbench OpenCL test, the Tesla P40 scores 62,017 points against 56,135 points for the CMP 50HX. That is a 10.5% advantage for the older Pascal-based card. While this is a solid lead, it is not an overwhelming one; both cards post scores that place them in the upper tier of the database, with the P40 sitting at the 89th percentile and the CMP 50HX at the 86th percentile among all GPUs.

The Geekbench Vulkan test tells a very different story. Here the Tesla P40 scores 68,172 points, while the CMP 50HX manages only 47,445 points. The delta expands to a massive 43.7% in favor of the P40. This is not a narrow victory; it is a decisive gap that suggests the CMP 50HX struggles considerably with Vulkan workloads relative to its OpenCL performance. The P40, by contrast, improves its score from OpenCL to Vulkan by roughly 10%, while the CMP 50HX drops by roughly 15% between the two APIs.

Looking at the overall average benchmark scores, the Tesla P40 averages 65,095 points, while the CMP 50HX averages 51,790 points. That is a 25.7% gap in aggregate performance. The P40's nearest rivals in the database include the AMD Radeon VII at 66,004 points (1.4% above the P40), the AMD Radeon Pro WX 9100 at 64,212 points (1.4% below), and the NVIDIA CMP 30HX at 63,842 points (2% below). The CMP 50HX, meanwhile, sits close to the AMD Radeon RX 6900 XT at 50,951 points (1.6% above the 50HX) and the AMD Radeon RX Vega 64 at 50,001 points (3.6% above it).

The win tally is straightforward: the Tesla P40 takes both tests, giving it 2 wins and 0 losses in this head-to-head. The Vulkan result is particularly notable because it is the single largest margin in either direction, and it drives the overall average score difference well beyond what either card's OpenCL result alone would suggest.

FAQ

Q: Which GPU wins the OpenCL benchmark?

A: The NVIDIA Tesla P40 wins with a score of 62,017 against the NVIDIA CMP 50HX's 56,135, a 10.5% advantage.

Q: How large is the Vulkan performance gap?

A: The Tesla P40 scores 68,172 in Geekbench Vulkan, while the CMP 50HX scores 47,445. The P40 leads by 43.7%, which is the largest margin in this comparison.

Q: What is the average benchmark score for each card?

A: The Tesla P40 has an average benchmark score of 65,095, while the CMP 50HX averages 51,790. The P40's average is about 25.7% higher.

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

A: The Tesla P40 sits at the 89th percentile, while the CMP 50HX sits at the 86th percentile. Both are in the upper tier, but the P40 is clearly positioned higher.

Q: Which card has a higher boost clock?

A: The CMP 50HX has a boost clock of 1545 MHz, which is slightly higher than the Tesla P40's boost clock of 1531 MHz.

Q: Do both cards have the same memory size?

A: No. The Tesla P40 has 24 GB of GDDR5 memory, while the CMP 50HX has 10 GB of GDDR6 memory.

Where Each One Wins

The Tesla P40 wins in every benchmark category recorded. Its strongest showing is in Vulkan, where the 43.7% lead over the CMP 50HX is the kind of margin that defines a category. This suggests the P40 is the better choice for any workload that leverages the Vulkan API, whether that involves compute tasks or graphics-adjacent operations.

The P40's OpenCL win is more modest at 10.5%, but still decisive. For users prioritizing OpenCL-based compute, the P40 remains ahead, though the CMP 50HX is closer in this specific scenario. The P40 also holds a significant memory capacity advantage at 24 GB versus 10 GB, which matters for workloads that require large datasets to reside on the GPU itself.

The CMP 50HX does not win any benchmark in this head-to-head. However, its profile shows areas where it is competitive. Its memory bandwidth is higher at 560.0 GB/s versus the P40's 347.1 GB/s, and its FP16 throughput is substantially higher at 22.15 TFLOPS versus the P40's 183.7 GFLOPS. For workloads that are bandwidth-bound or that rely heavily on half-precision arithmetic, the CMP 50HX has a theoretical edge, even though the recorded benchmark scores do not reflect a win in the tested APIs.

The CMP 50HX also supports hardware ray tracing and tensor cores, with 56 RT cores and 448 tensor cores, features entirely absent from the Pascal-based P40. For applications that use those dedicated units, the CMP 50HX is the only one of the two that can accelerate them. The P40's advantage lies in raw raster and compute throughput in the tested APIs, while the CMP 50HX's strengths are in specialized features and memory bandwidth.

Specification Differences

The two cards differ across nearly every major specification category. The Tesla P40 uses the GP102 chip built on the Pascal architecture, fabricated on a 16 nm process at TSMC. The CMP 50HX uses the TU102 chip on the Turing architecture, fabricated on a 12 nm process, also at TSMC. The transistor counts differ significantly: the P40 has 11,800 million transistors on a 471 mm² die, while the CMP 50HX has 18,600 million transistors on a 754 mm² die. Transistor density is similar, at 25.1M per mm² for the P40 and 24.7M per mm² for the CMP 50HX.

Clock speeds are close. The P40 runs at 1303 MHz base and 1531 MHz boost. The CMP 50HX runs at 1350 MHz base and 1545 MHz boost. Memory clocks differ: the P40's GDDR5 runs at 1808 MHz (7.2 Gbps effective), while the CMP 50HX's GDDR6 runs at 1750 MHz (14 Gbps effective).

Memory configuration is a major split. The P40 has 24 GB on a 384-bit bus, yielding 347.1 GB/s of bandwidth. The CMP 50HX has 10 GB on a 320-bit bus, yielding 560.0 GB/s of bandwidth. Despite having less than half the capacity, the CMP 50HX delivers 61% more bandwidth.

Compute resources also differ. The P40 has 3840 shading units, 240 texture mapping units, and 96 render output units. The CMP 50HX has 3584 shading units, 192 TMUs, and 80 ROPs. The P40 also has higher pixel rate at 147.0 GPixel/s versus 123.6 GPixel/s, and higher texture rate at 367.4 GTexel/s versus 296.6 GTexel/s. FP32 throughput is close, with the P40 at 11.76 TFLOPS and the CMP 50HX at 11.07 TFLOPS. FP16 is where they diverge sharply: the P40 delivers 183.7 GFLOPS at a 1:64 ratio, while the CMP 50HX delivers 22.15 TFLOPS at a 2:1 ratio.

Both cards consume 250 W and are dual-slot designs. The P40 uses a single 8-pin EPS power connector, while the CMP 50HX requires two 8-pin connectors. Both list a 600 W suggested PSU. The P40 uses a PCIe 3.0 x16 interface, while the CMP 50HX uses PCIe 1.0 x4, a significant bandwidth limitation for the newer card. Physical dimensions are close: both are 267 mm long, but the P40 is 111 mm high while the CMP 50HX is 116 mm high and 35 mm wide. Neither card has display outputs.

Architecture Differences

The architectural gap between these two cards is generational. The Tesla P40 belongs to the Tesla Pascal generation, released in September 2016, with the Pascal architecture. The CMP 50HX belongs to the Mining GPUs generation, released in June 2021, with the Turing architecture. The P40's predecessor is Tesla Maxwell and its successor is Tesla Volta. The CMP 50HX has no recorded predecessor or successor in the database.

The process node is one of the clearest indicators of the generational shift. The P40 uses 16 nm TSMC, while the CMP 50HX uses 12 nm TSMC. The newer process allows the CMP 50HX to pack 18,600 million transistors into a 754 mm² die, compared to the P40's 11,800 million transistors on a 471 mm² die. The density is nearly identical, which suggests the larger die is simply a function of more logic and features rather than a more efficient layout.

The most consequential architectural difference is the introduction of dedicated hardware in the Turing design. The CMP 50HX includes 56 ray tracing cores and 448 tensor cores. The P40 has none of these. Ray tracing cores accelerate the bounding volume hierarchy traversal and ray-triangle intersection tests that are fundamental to real-time ray tracing workloads. Tensor cores accelerate matrix math, which is the basis of deep learning inference and training. The P40, lacking these units, must rely on its general-purpose FP32 and FP16 pipelines, which is why its FP16 throughput is so low at 183.7 GFLOPS (1:64 ratio) compared to the CMP 50HX's 22.15 TFLOPS (2:1 ratio). The 1:64 ratio on the P40 means FP16 runs at 1/64th the rate of FP32, a deliberate design choice for a compute card focused on FP32 workloads. The 2:1 ratio on the CMP 50HX means FP16 runs at twice the rate of FP32, enabled by the tensor core design.

The DirectX support also reflects the architectural leap. The P40 supports DirectX 12 (12_1), while the CMP 50HX supports DirectX 12 Ultimate (12_2). Both cards support OpenGL 4.6 and Vulkan 1.4. The CMP 50HX's support for the newer DirectX feature level is tied directly to its Turing architecture, which added mesh shaders, variable rate shading, and other features that the Pascal architecture cannot provide.

The memory architecture is also a generational shift. The P40 uses GDDR5 on a 384-bit bus, while the CMP 50HX uses GDDR6 on a 320-bit bus. The newer GDDR6 memory operates at a higher effective data rate of 14 Gbps versus 7.2 Gbps, which is why the CMP 50HX achieves higher bandwidth despite a narrower bus. The PCIe interface difference is notable: the P40 uses PCIe 3.0 x16, while the CMP 50HX uses PCIe 1.0 x4. This makes the CMP 50HX more sensitive to host-side data transfer bottlenecks, as its interface bandwidth is a fraction of what the P40 can use.

The recorded benchmark results show the P40 winning both tests despite the CMP 50HX's newer architecture and dedicated hardware. This indicates that for the tested OpenCL and Vulkan workloads, raw shading throughput and memory capacity matter more than tensor cores or ray tracing units. The CMP 50HX's strengths would only show in workloads specifically designed to use its specialized hardware, which are not represented in these two benchmark tests.