NVIDIA CMP 50HX vs NVIDIA Tesla M40 24 GB Comparison

FAQ

Q: How does the NVIDIA CMP 50HX compare to the NVIDIA Tesla M40 24 GB in average benchmark score?

A: The CMP 50HX has an average benchmark score of 51790, while the Tesla M40 24 GB scores 41707. That places the CMP 50HX about 24.2% higher on average.

Q: Which GPU wins the OpenCL test and by how much?

A: The CMP 50HX wins Geekbench OpenCL with a score of 56135 versus 37439 for the Tesla M40 24 GB, a delta of 49.9%.

Q: Is the Vulkan result closer than OpenCL?

A: Yes. In Vulkan, the CMP 50HX scores 47445 versus 45975 for the Tesla M40 24 GB, a margin of only 3.2%.

Q: What are the memory capacities and types for each card?

A: The CMP 50HX has 10 GB of GDDR6 on a 320-bit bus, while the Tesla M40 24 GB has 24 GB of GDDR5 on a 384-bit bus.

Q: How do their percentile rankings differ?

A: The CMP 50HX sits at the 86th percentile among all GPUs, while the Tesla M40 24 GB sits at the 83rd percentile.

Q: Which card has a higher transistor count and what is the node difference?

A: The CMP 50HX packs 18,600 million transistors on a 12 nm process, whereas the Tesla M40 24 GB has 8,000 million transistors on a 28 nm process.

Architecture Differences

The two cards represent fundamentally different eras of NVIDIA design. The CMP 50HX uses the TU102 chip built on the Turing architecture, manufactured at 12 nm by TSMC. It packs 18,600 million transistors onto a 754 mm² die, giving a transistor density of 24.7 million per square millimeter. In contrast, the Tesla M40 24 GB uses the GM200 chip on the Maxwell 2.0 architecture, also from TSMC but at a 28 nm process. That die is 601 mm², holding 8,000 million transistors for a density of 13.3 million per square millimeter.

The compute feature sets diverge sharply. The CMP 50HX includes 56 RT cores and 448 tensor cores, enabling hardware-accelerated ray tracing and tensor operations. The Tesla M40 24 GB has neither RT cores nor tensor cores, reflecting its older Maxwell design. The shading unit counts also differ: 3584 shading units on the CMP 50HX versus 3072 on the Tesla M40 24 GB. Both have 192 texture mapping units, but the Tesla M40 24 GB has more raster operation units, 96 versus 80.

Clock behavior separates the two as well. The CMP 50HX runs a base of 1350 MHz and a boost of 1545 MHz, while the Tesla M40 24 GB runs a base of 948 MHz and a boost of 1112 MHz. Memory clocks are also distinct: the CMP 50HX lists a memory clock of 1750 MHz (14 Gbps effective), while the Tesla M40 24 GB lists 1502 MHz (6 Gbps effective). The CMP 50HX supports DirectX 12 Ultimate (12_2) and Vulkan 1.4, while the Tesla M40 24 GB supports DirectX 12 (12_1) and Vulkan 1.4. Both are OpenGL 4.6.

The bus interface and power delivery differ. The CMP 50HX uses PCIe 1.0 x4, which is a severe bottleneck for a modern GPU, while the Tesla M40 24 GB uses PCIe 3.0 x16. Power connectors are 2x 8-pin on the CMP 50HX versus a single 8-pin EPS on the Tesla M40 24 GB. Both have a 250 W TDP and a suggested PSU of 600 W. Both are dual-slot cards with no display outputs, and both are end-of-life products. The CMP 50HX released on June 23, 2021, while the Tesla M40 24 GB released on November 9, 2015. The Tesla M40 24 GB has a predecessor (Tesla Kepler) and a successor (Tesla Pascal), while the CMP 50HX has neither listed.

The Verdict

The data points to a clear performance hierarchy. The CMP 50HX wins both recorded benchmark tests, and its average benchmark score of 51790 is roughly 24.1% higher than the Tesla M40 24 GB's 41775. In OpenCL, the margin is particularly large at 49.9%, showing a substantial compute advantage for the Turing card.

For workloads that stress OpenCL compute, the CMP 50HX is the stronger card by a wide margin. The 11.07 TFLOPS of FP32 performance versus 6.832 TFLOPS on the Tesla M40 24 GB, combined with a much higher boost clock and more shading units, reinforces this. The CMP 50HX also has tensor cores and RT cores, which could matter for applications that use those features, though the recorded benchmarks do not test them directly.

However, the Tesla M40 24 GB is not without arguments. It offers 24 GB of memory versus 10 GB on the CMP 50HX. That extra capacity could be decisive for workloads where memory size outweighs raw speed, such as holding very large datasets or models in VRAM. Its 384-bit bus, though older, gives a wider path, but the effective bandwidth is lower: 288.4 GB/s versus 560.0 GB/s on the CMP 50HX. The Tesla M40 24 GB also uses PCIe 3.0 x16, which is a far more practical interface than the CMP 50HX's PCIe 1.0 x4, meaning host transfer speeds could bottleneck the CMP 50HX in real systems.

For most compute tasks, the CMP 50HX is the better pick based on raw performance numbers. For memory-capacity-bound tasks, the Tesla M40 24 GB has a clear capacity advantage. The choice is essentially speed versus capacity. The CMP 50HX is the faster card; the Tesla M40 24 GB is the larger-memory card.

Specification Differences

The differences in specifications are extensive. The CMP 50HX uses the TU102 chip on Turing, while the Tesla M40 24 GB uses GM200 on Maxwell 2.0. Process node is 12 nm versus 28 nm. Transistor count is 18,600 million vs 8,000 million, and die size is 754 mm² vs 601 mm². Transistor density is 24.7M per mm² vs 13.3M per mm².

Clock speeds differ: the CMP 50HX runs 1350 MHz base and 1545 MHz boost, while the Tesla M40 24 GB runs 948 MHz base and 1112 MHz boost. Memory clocks are 1750 MHz (14 Gbps effective) vs 1502 MHz (6 Gbps effective). Memory configuration varies: 10 GB GDDR6 on a 320-bit bus vs 24 GB GDDR5 on a 384-bit bus, yielding bandwidth of 560.0 GB/s vs 288.4 GB/s.

Compute units differ: 3584 shading units vs 3072, 192 TMUs vs 192, 80 ROPs vs 96. The CMP 50HX has 56 RT cores and 64 tensor cores; the Tesla M40 24 GB has none. Pixel rates are 123.6 GPixel/s vs 106.8 GPixel/s, texture rates 296.6 GTexel/s vs 213.5 GTexel/s. FP32 is 11.07 TFLOPS vs 6.832 TFLOPS. FP16 is 22.15 TFLOPS (2:1) on the CMP 50HX, not present on the Tesla M40 24 GB.

Power and physical specs: both are 250 W TDP and dual-slot, but the CMP 50HX uses 2x 8-pin while the Tesla M40 24 GB uses 8-pin EPS. The CMP 50HX has PCIe 1.0 x4, the Tesla M40 24 GB has PCIe 3.0 x16. Both have no display outputs. Dimensions: both are 267 mm long, the CMP 50HX is 116 mm high and 35 mm wide, while the Tesla M40 24 GB has no listed height or width. The CMP 50HX supports DirectX 12 Ultimate (12_2) versus DirectX 12 (12_1) on the Tesla M40 24 GB. Both support OpenGL 4.6 and Vulkan 1.4.

Head-to-Head Benchmarks

The recorded data shows the CMP 50HX winning both tests, but with very different margins. In the Geekbench OpenCL test, the CMP 50HX scores 56135 against 37439 for the Tesla M40 24 GB. That is a 49.9% advantage, which is a dominant result. The CMP 50HX delivers significantly more raw compute power, which is consistent with its higher transistor count, newer architecture, and faster clocks.

In the Geekbench Vulkan test, the gap narrows dramatically. The CMP 50HX scores 47445 versus 45975 for the Tesla M40 24 GB, a delta of only 3.2%. This suggests that in Vulkan workloads, the older Maxwell card remains competitive, possibly due to its wider memory bus and higher ROP count. The 24 GB memory capacity might also help in Vulkan scenarios that are memory-heavy.

The average benchmark score reflects the OpenCL-heavy weighting of the two tests. The CMP 50HX averages 51790, while the Tesla M40 24 GB averages 41775. In the nearest rival comparison, the CMP 50HX sits 1.6% above the AMD Radeon RX 6900 XT (50951), 3.6% above the RX Vega 64 (50001), 3.7% above the RTX 5070 Ti (49957), and 4.1% above the Intel Arc A550M (49737). The Tesla M40 24 GB is 0.5% below another Tesla M40 (which scores 41897), 1.3% above the RTX 3080 Ti (41187), 2.0% above the Radeon Pro 5300 (40870), and 2.4% below the Radeon RX 7650 GRE (42723).

The delta percentages between the two cards are consistent with the score differences. In the only two head-to-head tests, the CMP 50HX wins both, giving it a 2-0 record. The Tesla M40 24 GB has no wins against the CMP 50HX.

Where Each One Wins

The CMP 50HX wins in raw compute performance. Its FP32 performance is about 62% higher than the Tesla M40 24 GB (11.07 TFLOPS vs 6.832 TFLOPS). Its pixel rate is 123.6 GPixel/s versus 106.8 GPixel/s, a gain of roughly 15.7%. Its texture rate is 296.6 GTexel/s versus 213.5 GTexel/s, a 38.9% advantage. Memory bandwidth is 560.0 GB/s versus 288.4 GB/s, which is nearly double. The CMP 40 also has FP16 support at 22.15 TFLOPS, which the Tesla M40 24 GB lacks entirely.

The CMP 50HX also wins on transistor density and process node, which typically translate to better energy efficiency per transistor, though both cards share the same 250 W TDP. Its higher boost clock, 1545 MHz vs 1112 MHz, contributes to its compute lead.

The Tesla M40 24 GB wins on memory capacity and bus width. It has 24 GB versus 10 GB, which is 140% more memory. Its 384-bit bus is wider than the 320-bit bus on the CMP 50HX, which can help in certain memory-access patterns. It also has more ROPs, 96 versus 80, which could favor fill-rate-bound tasks. The Tesla M40 24 GB also uses PCIe 3.0 x16, whereas the CMP 50HX uses PCIe 1.0 x4, meaning host-to-device transfers are likely faster on the Tesla M40 24 GB, even though the recorded benchmarks do not capture this.

In the Vulkan benchmark, the Tesla M40 24 GB is much closer to the CMP 50HX, losing only by 3.2%, which suggests its architecture is less disadvantaged in Vulkan tasks. For workloads that are memory-capacity-bound or that rely on wide memory access, the Tesla M40 24 GB is the better fit. For compute-bound workloads that use OpenCL or FP32 throughput, the CMP 50HX is clearly superior.

The data also shows that the Tesla M40 24 GB is positioned differently in the market. Its nearest rivals are mostly newer cards like the RTX 3080 Ti, but it is competitive with them, being only 1.3% behind. The CMP 50HX, on the other hand, is above the RX 6900 XT and RTX 5070 Ti in average score. This indicates that the CMP 50HX belongs to a higher performance tier, while the Tesla M40 24 GB sits in a lower tier despite its large memory capacity.