NVIDIA CMP 50HX vs NVIDIA RTX A3000 Mobile Comparison

Head-to-Head Benchmarks

The recorded data shows a decisive overall victory for the NVIDIA RTX A3000 Mobile, which wins both benchmark comparisons against the NVIDIA CMP 50HX. In the Geekbench OpenCL test, the RTX A3000 Mobile scores 79,091 points against 56,135 for the CMP 50HX, a margin of 40.9%. This is a substantial gap, placing the mobile workstation part well ahead of the mining-focused card in general-purpose compute workloads.

The Vulkan results tell a similar story, though with a narrower margin. The RTX A3000 Mobile posts 61,189 points, while the CMP 50HX manages 47,445, giving the A3000 a 29% advantage. The delta between the two tests is notable: the OpenCL gap is nearly 12 percentage points larger than the Vulkan gap, suggesting the A3000's architecture handles certain compute paths more efficiently relative to the CMP 50HX. Both results, however, are unambiguous in favor of the mobile part.

Context from the database's nearest rival comparisons reinforces this hierarchy. The RTX A3000 Mobile has an average benchmark score of 70,140 and sits at the 91st percentile of all GPUs. Its nearest rivals include the NVIDIA Quadro P6000 at 69,986 (0.2% behind), the AMD Radeon Pro WX 8200 at 69,870 (0.4% behind), and the AMD Radeon RX 6600 LE at 70,829 (1% ahead). The CMP 50HX, by contrast, has an average score of 51,790 and ranks at the 86th percentile. Its nearest rivals are the AMD Radeon RX 6900 XT at 50,951 (1.6% behind), the AMD Radeon RX Vega 64 at 50,001 (3.6% behind), the NVIDIA GeForce RTX 5070 Ti at 49,957 (3.7% behind), and the Intel Arc A550M at 49,737 (4.1% behind). The A3000 Mobile is not merely faster than the CMP 50HX; it operates in a different performance tier, competing with high-end workstation parts from the previous generation rather than with mining-optimized hardware.

The average benchmark score difference between the two cards is 18,350 points, which represents a 35.4% advantage for the RTX A3000 Mobile relative to the CMP 50HX's average. This is consistent with the individual test deltas, confirming that the OpenCL and Vulkan results are not outliers but reflective of a consistent performance differential across the database's measurement suite.

Where Each One Wins

The RTX A3000 Mobile wins in every measured category, so the use-case split is largely defined by the magnitude of its advantages and the specific workloads where the CMP 50HX comes closest. In Vulkan, the A3000's 29% lead is the smaller of the two margins. Vulkan is often used in cross-platform graphics and compute applications, and the narrower gap here suggests that the CMP 50HX's Turing architecture still handles certain graphics-oriented tasks respectably, even if it cannot match the Ampere-based A3000.

In OpenCL, the A3000's 40.9% advantage is the more decisive result. OpenCL workloads tend to stress raw compute throughput, memory bandwidth, and driver scheduling. The A3000's higher FP32 throughput of 10.08 TFLOPS, combined with its 264.0 GB/s of memory bandwidth, gives it a clear edge in general-purpose compute. The CMP 50HX actually has higher peak FP32 at 11.07 TFLOPS and much higher memory bandwidth at 560.0 GB/s, yet it still loses by a wide margin in the recorded tests. This suggests that real-world benchmark performance does not scale linearly with theoretical specifications, and factors such as driver maturity, memory latency, and workload characteristics play a significant role.

For users prioritizing raw compute in OpenCL-centric environments, the RTX A3000 Mobile is the stronger choice by a wide margin. For those working primarily with Vulkan-based applications, the A3000 still wins, but the CMP 50HX is comparatively less far behind. The CMP 50HX has no display outputs, which limits its utility to compute-only or mining scenarios, whereas the A3000 Mobile's outputs are portable-device dependent, making it suitable for mobile workstation deployments. The A3000 also supports a broader range of visual outputs by virtue of being a mobile part, even though the exact connectors depend on the host laptop.

The CMP 50HX's only realistic use case is headless compute or mining, where its lack of display outputs is not a handicap. However, the benchmark data shows that even in that narrow role, it is outperformed by the A3000 Mobile in both OpenCL and Vulkan, meaning there is no measured workload where the CMP 50HX comes out ahead. Its higher memory capacity of 10 GB and bandwidth of 560.0 GB/s could theoretically benefit memory-bound tasks, but the recorded scores do not reflect any such advantage materializing in the database's tests.

FAQ

Q: Which GPU has the higher average benchmark score?

A: The NVIDIA RTX A3000 Mobile, with an average score of 70,140 compared to the CMP 50HX's 51,790. This places the A3000 at the 91st percentile of all GPUs, while the CMP 50HX sits at the 86th percentile.

Q: How large is the performance gap in OpenCL?

A: The RTX A3000 Mobile scores 79,091 in Geekbench OpenCL, while the CMP 50HX scores 56,135. That is a 40.9% advantage for the A3000 Mobile.

Q: Does the CMP 50HX win any benchmark comparison?

A: No. The database records two head-to-head tests, Geekbench OpenCL and Geekbench Vulkan, and the RTX A3000 Mobile wins both. The CMP 50HX has zero wins in the head-to-head comparison.

Q: What is the difference in Vulkan performance?

A: The RTX A3000 Mobile scores 61,189 in Geekbench Vulkan, against 47,445 for the CMP 50HX, a 29% margin in favor of the A3000.

Q: How does the RTX A3000 Mobile compare to its nearest rivals?

A: Its closest rival is the AMD Radeon RX 6600 LE, which is 1% ahead. The NVIDIA Quadro P6000 is 0.2% behind, the AMD Radeon Pro WX 8200 is 0.4% behind, and the NVIDIA CMP 90HX is 1.7% behind.

Q: How does the CMP 50HX compare to its nearest rivals?

A: The CMP 50HX leads all four of its nearest rivals. The AMD Radeon RX 6900 XT is 1.6% behind, the AMD Radeon RX Vega 64 is 3.6% behind, the NVIDIA GeForce RTX 5070 Ti is 3.7% behind, and the Intel Arc A550M is 4.1% behind.

Specification Differences

The two cards differ across nearly every major specification category. The RTX A3000 Mobile uses the GA104 chip built on an 8 nm process at Samsung, while the CMP 50HX uses the TU102 chip on a 12 nm process at TSMC. The A3000 has 17,400 million transistors on a 392 mm² die, giving a transistor density of 44.4 million per mm². The CMP 50HX has more transistors at 18,600 million, but on a much larger 754 mm² die, yielding a lower density of 24.7 million per mm².

Clock speeds differ substantially. The A3000 Mobile has a base clock of 600 MHz and a boost clock of 1230 MHz. The CMP 50HX runs significantly higher, with a base of 1350 MHz and a boost of 1545 MHz. Memory clocks also favor the CMP 50HX: it operates at 1750 MHz with 14 Gbps effective speed, while the A3000 runs at 1375 MHz with 11 Gbps effective.

Memory configuration is another major differentiator. The A3000 Mobile has 6 GB of GDDR6 on a 192-bit bus, delivering 264.0 GB/s bandwidth. The CMP 50HX has 10 GB of GDDR6 on a 320-bit bus, delivering 560.0 GB/s, more than double the bandwidth. The CMP also has a larger L2 cache architecture to support its wider memory subsystem, though the recorded data does not quantify cache sizes.

The compute unit counts differ in interesting ways. The A3000 has 4096 shading units, 128 TMUs, and 64 ROPs. The CMP 50HX has fewer shading units at 3584, but more TMUs at 192 and more ROPs at 80. The A3000 has 32 RT cores and 128 tensor cores, while the CMP has 56 RT cores and 448 tensor cores, giving the Turing part a large advantage in both ray tracing and tensor operations on paper. Pixel and texture rates reflect this: the CMP achieves 123.6 GPixel/s and 296.6 GTexel/s, while the A3000 manages 78.72 GPixel/s and 157.4 GTexel/s.

FP32 performance is close, with the CMP at 11.07 TFLOPS versus 10.08 TFLOPS for the A3000. FP16 performance, however, diverges sharply: the CMP delivers 22.15 TFLOPS at a 2:1 ratio, while the A3000 delivers 10.08 TFLOPS at a 1:1 ratio. Power consumption is a stark contrast: the A3000 Mobile is rated at 70 W with no power connectors, while the CMP 50HX draws 250 W and requires two 8-pin connectors with a suggested 600 W power supply.

The CMP 50HX is a dual-slot card measuring 267 mm in length, 116 mm in height, and 35 mm in width. The A3000 Mobile has no recorded dimensions, as it is a mobile component whose size depends on the host device. The bus interfaces also differ: the A3000 uses PCIe 4.0 x16, while the CMP uses PCIe 1.0 x4, a significant bottleneck for the mining card. Display outputs differ as well: the A3000 is portable-device dependent, while the CMP has no outputs at all.

Architecture Differences

The architectural split between these two GPUs reflects two different NVIDIA generations and design philosophies. The RTX A3000 Mobile is built on the Ampere architecture, specifically the GA104 chip, and belongs to the Ampere-MW (Ax000) generation. It is manufactured on Samsung's 8 nm process. The CMP 50HX, by contrast, uses the Turing architecture with the TU102 chip and belongs to NVIDIA's Mining GPUs generation, built on TSMC's 12 nm process. These process differences explain the transistor density gap: the A3000 packs 44.4 million transistors per mm², nearly double the CMP's 24.7 million per mm², despite the CMP having more total transistors.

The RTX A3000 Mobile's Ampere architecture is a direct successor to the Quadro Turing-M line and was itself succeeded by Ada-MW, per the database's generation tracking. The CMP 50HX has no recorded predecessor or successor, reflecting its status as a standalone mining product. The A3000 Mobile was released on 2021-04-11, while the CMP 50HX followed on 2021-06-23, both now marked end-of-life.

The FP16 ratio difference is a key architectural marker. The A3000 Mobile's 1:1 FP16 to FP32 ratio is characteristic of Ampere's design, where FP16 throughput matches FP32. The CMP 50HX's 2:1 ratio is a Turing trait, doubling FP16 throughput to 22.15 TFLOPS. This means the CMP 50HX is theoretically better suited to FP16-heavy workloads such as certain AI inference tasks, though its lower shading unit count and older architecture limit its overall benchmark performance.

The RT core and tensor core counts also reflect generational differences. The CMP 50HX has 56 RT cores and 448 tensor cores, both higher than the A3000's 32 and 128 respectively. However, the A3000's Ampere tensor cores are a newer design, and the benchmark results suggest that the A3000's overall architecture delivers better real-world performance despite the CMP's numerical advantages in these specific units.

The bus interface difference is particularly telling. The A3000 Mobile uses PCIe 4.0 x16, offering substantial bandwidth for data transfer with the host system. The CMP 50HX uses PCIe 1.0 x4, an extremely limited interface that predates modern standards by generations. This makes the CMP 50HX poorly suited for general-purpose computing where data must move frequently between the GPU and system memory. It is designed for mining workloads, which are largely self-contained on the GPU and do not require significant host communication.

Both cards support DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4, so API-level compatibility is identical. The practical differences lie in the underlying hardware: process node, architecture generation, memory subsystem, and power delivery. The A3000 Mobile's 70 W TDP and lack of power connectors make it suitable for mobile workstations, while the CMP 50HX's 250 W TDP and dual 8-pin connectors require a desktop power supply and a system capable of dissipating significant heat. The CMP's dual-slot cooler and 267 mm length are standard for a desktop card, whereas the A3000's thermal solution is entirely dependent on the laptop vendor's design.

The architecture differences ultimately explain the benchmark results. The A3000 Mobile's newer 8 nm process, higher transistor density, and PCIe 4.0 x16 interface contribute to its 40.5% average score advantage, while the CMP 50HX's older 12 nm process and PCIe 1.0 x4 interface hold it back despite its larger memory pool and higher clock speeds. The benchmark outcomes align with the architectural progression from Turing to Ampere, with the newer generation delivering superior measured performance across both OpenCL and Vulkan.