NVIDIA CMP 40HX vs NVIDIA Tesla V100 PCIe 32 GB Comparison

Head-to-Head Benchmarks

The recorded data shows a decisive performance margin for the NVIDIA Tesla V100 PCIe 32 GB across both benchmark workloads. In the Geekbench OpenCL test, the Tesla V100 scores 168,763 points against the CMP 40HX's 93,395 points, a delta of 80.7%. This is the largest advantage observed in the comparison, and it reflects a substantial difference in raw compute throughput for general-purpose GPU workloads.

The Vulkan result narrows the gap somewhat but still favors the Tesla V100 decisively. The V100 posts 131,847 points, while the CMP 40HX manages 77,879 points, a 69.3% difference. The fact that the Vulkan delta is smaller than the OpenCL delta suggests the CMP 40HX's architecture handles graphics-API-oriented tasks relatively better than its compute-oriented tasks, though it remains far behind in absolute terms.

Looking at the average benchmark score, the Tesla V100 records 150,305 points, which places it in the 96th percentile of all GPUs in the database. The CMP 40HX, by contrast, has an average score of 85,637 points and sits in the 93rd percentile. While both are high-percentile performers, the raw score difference is approximately 75.5% in favor of the V100 when comparing the two averages directly.

The nearest rivals for each card provide useful context for interpreting these scores. The Tesla V100's closest competitors include the AMD Radeon Pro W6800X at 160,671 points (6.5% ahead of the V100), the NVIDIA A100 PCIe 40 GB at 162,504 points (7.5% ahead), and the NVIDIA A10G at 151,963 points (1.1% behind). The AMD Instinct MI100 trails the V100 by 8.1% with a score of 139,035. The V100 holds its own against this field, sitting within single-digit percentage points of the top performers.

The CMP 40HX's nearest rivals are clustered much closer to its score. The AMD Radeon PRO W7600 scores 87,108 points, just 1.7% ahead of the CMP 40HX. The NVIDIA Quadro GP100 is 2.1% ahead at 87,445 points. On the trailing side, the AMD Radeon PRO W6600 is 4.4% behind the CMP 40HX, and the AMD Radeon Pro Vega 64X is 5.8% behind. This tight cluster indicates the CMP 40HX sits in a competitive mid-range segment, but it is nowhere near the performance class occupied by the Tesla V100.

Architecture Differences

The two cards derive from entirely different NVIDIA architectures and process nodes, which explains the performance gap. The Tesla V100 uses the GV100 chip built on Volta architecture, manufactured on a 12 nm process at TSMC. It integrates 21,100 million transistors on a die size of 815 mm², yielding a transistor density of 25.9 million per square millimeter. The CMP 40HX uses the TU106 chip on Turing architecture, also 12 nm at TSMC, but with just 10,800 million transistors on a 445 mm² die, for a density of 24.3 million per square millimeter.

The compute resources differ dramatically. The V100 carries 5,120 shading units, 320 texture mapping units, and 128 raster output units. The CMP 40HX has 2,304 shading units, 144 TMUs, and 64 ROPs. The V100 also features 640 tensor cores, while the CMP 40HX includes 288 tensor cores plus 36 RT cores. The V100 has no RT cores, reflecting its compute-first design. These raw counts explain why the V100's FP32 throughput reaches 14.13 TFLOPS versus the CMP 40HX's 7.603 TFLOPS, a near 2x difference. The FP16 figures follow the same pattern: 28.26 TFLOPS for the V100 versus 15.21 TFLOPS for the CMP 40HX, both at a 2:1 ratio.

Memory architecture is another fundamental differentiator. The V100 uses 32 GB of HBM2 on a 4096-bit bus, delivering 897.0 GB/s of bandwidth. The CMP 40HX uses 8 GB of GDDR6 on a 256-bit bus, providing 448.0 GB/s. The V100's memory bandwidth is exactly double the CMP 40HX's, which is a critical factor for large dataset workloads. The memory clock speeds also reflect the different memory types: the V100 runs at 876 MHz with 1752 Mbps effective, while the CMP 40HX runs at 1750 MHz with 14 Gbps effective.

Clock speeds favor the CMP 40HX in raw frequency. The CMP 40HX has a base clock of 1470 MHz and a boost of 1650 MHz, versus the V100's 1230 MHz base and 1380 MHz boost. However, the V100's much larger shader count and memory subsystem overcome the clock disadvantage. The pixel rate of the V100 is 176.6 GPixel/s versus 105.6 GPixel/s for the CMP 40HX, and the texture rate is 441.6 GTexel/s versus 237.6 GTexel/s.

Power characteristics also differ. The V100 has a 250 W TDP with dual-slot cooling and requires two 8-pin power connectors plus a 600 W suggested PSU. The CMP 40HX has a 185 W TDP, also dual-slot, with a single 8-pin connector and a 450 W suggested PSU. The CMP 40HX is physically smaller at 229 mm length, 111 mm height, and 35 mm width, while the V100's dimensions are not recorded.

The bus interface is a notable difference. The V100 uses PCIe 3.0 x16, while the CMP 40HX uses PCIe 1.0 x4. This severely limits the CMP 40HX's data transfer rates to the host system, which could bottleneck workloads that require frequent host-device communication. Neither card has display outputs, so both are strictly accelerator or compute products.

API support shows a generational split. The V100 supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. The CMP 40HX supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. The CMP 40HX's newer Turing architecture brings DirectX 12 Ultimate support with features like mesh shaders and ray tracing, which the older Volta card lacks. However, since neither card has display outputs, these API differences matter mainly for headless compute or rendering workloads.

Where Each One Wins

The Tesla V100 wins every benchmark in the head-to-head comparison, so the "where each one wins" analysis is about the magnitude and nature of those wins rather than any CMP 40HX victory. The V100 shows its largest advantage in OpenCL, a compute-centric API. The 80.7% delta indicates the V100's massive shader count, tensor cores, and doubled memory bandwidth provide a dominant edge in general-purpose compute tasks such as scientific simulation, machine learning training, and data processing.

The Vulkan benchmark shows a smaller but still substantial 69.3% advantage for the V100. Vulkan is a lower-level graphics and compute API, and the CMP 40HX's newer Turing architecture with RT cores and DirectX 12 Ultimate features narrows the gap slightly. This suggests the CMP 40HX may handle graphics-oriented workloads or newer rendering techniques relatively better than it handles pure compute, though it remains far behind in absolute performance.

The CMP 40HX's place in the database is best understood through its nearest rivals. It sits between the AMD Radeon PRO W7600 (1.7% ahead) and the AMD Radeon PRO W6600 (4.4% behind). This places it in a segment that could be suitable for lighter compute tasks, entry-level rendering, or workloads that do not require large memory capacities. Its 8 GB GDDR6 memory and 448.0 GB/s bandwidth are adequate for mid-range workloads, but the PCIe 1.0 x4 interface is a clear limitation for any data-intensive application.

The V100, by contrast, operates in a performance tier where it competes with the A100 and Radeon Pro W6800X. Its 32 GB HBM2 memory with 897.0 GB/s bandwidth is designed for large model training and inference tasks. The 96th percentile ranking places it among the top 4% of all GPUs in the database, while the CMP 40HX's 93rd percentile places it in the top 7%. Both are strong performers, but they are separated by a full performance class.

For users choosing a card strictly on benchmark data, the V100 is the clear choice for any workload that benefits from high FP32 throughput, large memory capacity, or high memory bandwidth. The CMP 40HX could be considered only for scenarios where its lower power draw (185 W vs 250 W), smaller physical footprint, or single 8-pin power requirement are decisive factors, and where the workload fits within 8 GB of memory.

FAQ

Q: How much faster is the Tesla V100 in the OpenCL benchmark?

A: The Tesla V100 scores 168,763 points versus 93,395 points for the CMP 40HX, a delta of 80.7% in favor of the V100.

Q: What is the average benchmark score difference between the two cards?

A: The Tesla V100 has an average benchmark score of 150,305 points, while the CMP 40HX averages 85,637 points. The V100's average is roughly 75.5% higher.

Q: Does the CMP 40HX win any benchmark in the head-to-head comparison?

A: No. The head-to-head data shows 2 wins for the Tesla V100 and 0 wins for the CMP 40HX across the recorded tests.

Q: What are the memory configurations of each card?

A: The Tesla V100 has 32 GB of HBM2 memory on a 4096-bit bus with 897.0 GB/s bandwidth. The CMP 40HX has 8 GB of GDDR6 memory on a 256-bit bus with 448.0 GB/s bandwidth.

Q: How do the nearest rivals compare to the CMP 40HX?

A: The AMD Radeon PRO W7600 is 1.7% ahead, the NVIDIA Quadro GP100 is 2.1% ahead, the AMD Radeon PRO W6600 is 4.4% behind, and the AMD Radeon Pro Vega 64X is 5.8% behind the CMP 40HX.

Q: What is the bus interface difference between the two cards?

A: The Tesla V100 uses PCIe 3.0 x16, while the CMP 40HX uses PCIe 1.0 x4. This means the CMP 40HX has a significantly narrower and slower interface to the host system.

The Verdict

The data presents an unambiguous performance hierarchy. The NVIDIA Tesla V100 PCIe 32 GB outperforms the NVIDIA CMP 40HX in every recorded benchmark by a wide margin, with deltas of 80.7% in OpenCL and 69.3% in Vulkan. The average benchmark score gap of roughly 75.5% reinforces that this is not a close contest.

The Tesla V100 is the appropriate choice for compute workloads that demand high FP32 throughput (14.13 TFLOPS), large memory capacity (32 GB HBM2), and high bandwidth (897.0 GB/s). Its 96th percentile ranking and competitive positioning against the A100 PCIe 40 GB (7.5% behind) and Radeon Pro W6800X (6.5% behind) show it remains a relevant high-end accelerator despite its end-of-life production status. Users with scientific computing, machine learning, or data processing needs should select the V100 based on its benchmark dominance.

The CMP 40HX, despite its end-of-life status, has a clear role for users who need a Turing architecture card with RT cores and DirectX 12 Ultimate support, but cannot accommodate the V100's power or size requirements. Its 185 W TDP, smaller physical dimensions, and single 8-pin connector make it easier to integrate into constrained systems. However, its 8 GB memory, 448.0 GB/s bandwidth, and PCIe 1.0 x4 interface limit its suitability to lighter workloads. The CMP 40HX's 93rd percentile ranking shows it performs well within its class, but its class is far below the V100's.

The verdict from the recorded data is straightforward: choose the Tesla V100 for maximum compute performance, and choose the CMP 40HX only when its lower power draw, compact size, or Turing-specific feature set are the deciding factors. The benchmark scores leave no room for ambiguity on raw capability.