AMD Radeon Pro Vega 64X vs NVIDIA CMP 40HX Comparison

The NVIDIA CMP 40HX and AMD Radeon Pro Vega 64X represent two divergent approaches to high-compute GPU design, separated by two years of architectural evolution. The data shows a clear overall winner in raw compute performance, but the AMD card retains specific advantages in memory capacity and bandwidth that matter for certain workloads.

Head-to-Head Benchmarks

The only directly comparable benchmark in the data set is Geekbench OpenCL, and it produces a decisive result. The NVIDIA CMP 40HX scores 93,395 points, while the AMD Radeon Pro Vega 64X scores 78,467 points. This represents a 19% advantage for the NVIDIA card, a substantial margin that places it clearly ahead in general-purpose compute workloads.

This performance gap is consistent with the broader benchmark landscape. The NVIDIA CMP 40HX achieves an average benchmark score of 85,637 across all tests, placing it in the 93rd percentile of all GPUs. The AMD Radeon Pro Vega 64X averages 80,959, sitting in the 92nd percentile. While both are elite performers, the NVIDIA card holds a 5.8% advantage in average score against the AMD card directly.

The CMP 40HX's nearest rival comparisons reinforce its standing. It trails the AMD Radeon PRO W7600 by only 1.7% and the NVIDIA Quadro GP100 by 2.1%, while sitting 4.4% ahead of the AMD Radeon PRO W6600. The Vega 64X, by contrast, sits 1.3% behind the same Radeon PRO W6600, and is 1.4% ahead of the NVIDIA GeForce RTX 5090 and 1.7% ahead of the Tesla P100 PCIe 16 GB.

The compute architecture explains much of this difference. The NVIDIA card delivers 7.603 TFLOPS of FP32 performance and 15.21 TFLOPS of FP16 performance, while the AMD card offers 12.03 TFLOPS FP32 and 24.05 TFLOPS FP16. The AMD card's higher theoretical throughput does not translate into OpenCL wins, suggesting that driver optimization and architecture efficiency favor the NVIDIA implementation in this specific benchmark.

The texture and pixel throughput numbers tell a similar story. The AMD card posts 375.8 GTexel/s against the NVIDIA card's 237.6 GTexel/s, and 93.95 GPixel/s against 105.6 GPixel/s. The NVIDIA card wins pixel fill rate despite having fewer ROPs at 64 versus 64, while the AMD card dominates texture throughput with 256 TMUs versus 144.

The Verdict

From the data alone, the NVIDIA CMP 40HX is the superior choice for OpenCL compute workloads. Its 19% lead in the head-to-head benchmark and 5.8% higher average score make it the safer pick for users prioritizing raw benchmark performance.

The AMD Radeon Pro Vega 64X does have one compelling advantage: memory. It offers 16 GB of HBM2 memory compared to 8 GB of GDDR6 on the NVIDIA card, with 512.0 GB/s bandwidth against 448.0 GB/s. For workloads that exceed 8 GB of working set, the AMD card becomes the only viable option between these two. The 2048-bit memory bus versus 256-bit also indicates fundamentally different memory architectures.

The NVIDIA card wins on efficiency and physical design. It draws 185 W versus 250 W for the AMD card, fits in a dual-slot form factor, and requires only a single 8-pin power connector. The AMD card is an integrated GPU package with no power connectors and portable-device-dependent display outputs, making it a specialized part for Apple Mac systems.

The CMP 40HX also carries newer API support, with DirectX 12 Ultimate (12_2) and Vulkan 1.4, while the Vega 64X supports DirectX 12 (12_1) and Vulkan 1.3. For users who need modern graphics API features, the NVIDIA card is the clear choice.

FAQ

Q: Which card is faster in OpenCL benchmarks?

A: The NVIDIA CMP 40HX scores 93,395 in Geekbench OpenCL, which is 19% higher than the AMD Radeon Pro Vega 64X's 78,467.

Q: How much memory does each card have?

A: The AMD Radeon Pro Vega 64X has 16 GB of HBM2 memory, while the NVIDIA CMP 40HX has 8 GB of GDDR6 memory.

Q: Which card has higher power consumption?

A: The AMD Radeon Pro Vega 64X draws 250 W, while the NVIDIA CMP 40HX consumes 185 W.

Q: Do both cards support ray tracing?

A: The NVIDIA CMP 40HX includes 36 RT cores and supports DirectX 12 Ultimate (12_2). The AMD Radeon Pro Vega 64X has no RT cores and supports DirectX 12 (12_1).

Q: What is the release date difference between these cards?

A: The AMD Radeon Pro Vega 64X was released on 2019-03-18, while the NVIDIA CMP 40HX was released on 2021-02-24.

Q: Which card has higher FP32 compute throughput?

A: The AMD Radeon Pro Vega 64X delivers 12.03 TFLOPS FP32, which is higher than the NVIDIA CMP 40HX's 7.603 TFLOPS, despite the NVIDIA card winning the OpenCL benchmark.

Specification Differences

The two cards differ across nearly every major specification category. The NVIDIA CMP 40HX uses the TU106 chip on a 12 nm TSMC process, while the AMD Radeon Pro Vega 64X uses the Vega 10 chip on a 14 nm GlobalFoundries process. The AMD chip has more transistors at 12,500 million versus 10,800 million, and a larger die at 495 mm² versus 445 mm².

Clock speeds favor the NVIDIA card. The CMP 40HX runs at a 1470 MHz base and 1650 MHz boost, while the Vega 64X operates at 1250 MHz base and 1468 MHz boost. Memory clocks are dramatically different: the NVIDIA card uses 1750 MHz (14 Gbps effective) GDDR6, while the AMD card uses 1000 MHz (2 Gbps effective) HBM2.

Shader resources heavily favor the AMD card. It contains 4096 shading units and 256 TMUs, while the NVIDIA card has 2304 shading units and 144 TMUs. Both have 64 ROPs. The NVIDIA card includes 36 RT cores and 288 tensor cores, while the AMD card has neither.

The memory subsystem differs fundamentally. The AMD card offers 16 GB of HBM2 on a 2048-bit bus with 512.0 GB/s bandwidth. The NVIDIA card offers 8 GB of GDDR6 on a 256-bit bus with 448.0 GB/s bandwidth.

Form factor and connectivity differ substantially. The NVIDIA card is dual-slot with a 229 mm length, 111 mm height, and 35 mm width, using a PCIe 1.0 x4 interface and a single 8-pin power connector. The AMD card is an integrated graphics package with no dimensions listed, no power connectors, and a PCIe 3.0 x16 interface. The NVIDIA card has no display outputs, while the AMD card's outputs are portable-device dependent.

Where Each One Wins

The NVIDIA CMP 40HX wins in OpenCL compute performance, delivering a 19% higher score in the head-to-head benchmark. It also wins on power efficiency at 185 W versus 250 W, on physical flexibility with its dual-slot design and standard power connector, and on API modernity with DirectX 12 Ultimate and Vulkan 1.4 support. Its RT and tensor cores make it suitable for workloads involving ray tracing or AI acceleration, though no specific benchmarks in the data confirm this advantage.

The AMD Radeon Pro Vega 64X wins on memory capacity and bandwidth. Its 16 GB of HBM2 at 512.0 GB/s doubles the capacity and exceeds the bandwidth of the NVIDIA card's 8 GB GDDR6 at 448.0 GB/s. This makes it the better choice for memory-bound workloads or large datasets that exceed 8 GB. Its higher theoretical compute throughput of 12.03 TFLOPS FP32 and 24.05 TFLOPS FP16 suggests it may perform better in compute tasks that are not well-served by the OpenCL benchmark, though the data does not directly confirm this.

The AMD card's 2048-bit memory bus and 375.8 GTexel/s texture rate indicate strengths in texture-heavy workloads, while the NVIDIA card's 105.6 GPixel/s pixel rate gives it an edge in pixel-fill-bound scenarios.

The release date difference also matters. The AMD card launched on 2019-03-18 as a Radeon Pro Mac part, while the NVIDIA card launched on 2021-02-24 as a mining GPU. The NVIDIA card's newer architecture and API support make it more future-proof for modern software, while the AMD card's integration into Mac systems makes it the only choice for that specific ecosystem.

For users who prioritize raw OpenCL performance, power efficiency, and modern API support, the NVIDIA CMP 40HX is the data-backed pick. For users who need more than 8 GB of memory, higher memory bandwidth, or compatibility with Apple Mac systems, the AMD Radeon Pro Vega 64X is the only option that fits those requirements. Both cards are end-of-life production, but their benchmark data remains relevant for comparison purposes.