NVIDIA Quadro K620 vs NVIDIA Quadro M500M Comparison

Head-to-Head Benchmarks

The recorded data shows a clear, consistent advantage for the NVIDIA Quadro K620 across both tested workloads. In the Geekbench OpenCL test, the K620 scores 6693 against the M500M’s 5986, a delta of 11.8%. The Vulkan test shows a similar pattern: the K620 posts 5870 versus 5222, translating to a 12.4% lead. These are not marginal differences; they represent a solid, repeatable performance gap in favor of the older desktop-oriented card.

Looking at the broader context, the K620’s average benchmark score sits at 6282, placing it in the 36th percentile of all GPUs. Its nearest rivals include the NVIDIA GeForce RTX 5070 Ti SUPER at 6270 (a 0.2% gap) and the AMD Radeon Pro WX 4100 at 6330 (a -0.8% gap). The M500M, by contrast, averages 5604, landing in the 32nd percentile. Its nearest competitor, the AMD FirePro M4000, scores 5537, which is 1.2% behind the M500M, while the NVIDIA GeForce GTX 765M trails by 1.9% at 5501. These percentile figures confirm that the K620 sits in a higher performance tier overall, even if the absolute deltas against its specific rivals are modest.

The head-to-head table lists two tests, and the K620 wins both. The wins are not close in relative terms: an 11.8% lead in OpenCL and a 12.4% lead in Vulkan. For professional workloads that leverage compute APIs, this gap is substantial. The M500M’s lower scores place it closer to older mobile gaming parts, as evidenced by its rival list, whereas the K620’s rivals include much more recent desktop GPUs. This suggests the K620 punches above its age, while the M500M sits firmly in the entry-level mobile segment.

One notable observation is that the K620’s average score of 6282 is within 0.8% of the AMD Radeon Pro WX 4100, a professional card from a later generation. The M500M’s average, however, is nearly 12% below the K620’s. In practical terms, any application that relies on OpenCL or Vulkan acceleration will show a measurable improvement on the K620, making it the stronger choice for compute-heavy tasks.

Architecture Differences

Both cards share the Maxwell architecture and are built on TSMC’s 28 nm process, but the similarities end there. The K620 uses the GM107 chip with 1,870 million transistors on a 148 mm² die, yielding a transistor density of 12.6M per mm². The M500M uses the GM108S chip, which is considerably smaller: 1,020 million transistors on a 77 mm² die, giving a density of 13.2M per mm². The smaller die and lower transistor count of the M500M reflect its mobile-oriented design, prioritizing power efficiency over raw throughput.

The memory subsystems differ significantly. The K620 has a 128-bit memory bus, while the M500M is limited to a 64-bit bus. Both use 2 GB of DDR3 memory at 900 MHz (1800 Mbps effective), but the K620’s wider bus delivers 28.80 GB/s of bandwidth, exactly double the M500M’s 14.40 GB/s. This bandwidth advantage is critical for texture-heavy workloads and large datasets, and it directly explains part of the K620’s benchmark lead.

Shading unit counts are identical at 384, but the rest of the pipeline differs. The K620 has 24 texture mapping units (TMUs) and 16 raster output units (ROPs), whereas the M500M has 16 TMUs and 8 ROPs. Consequently, the K620 achieves a pixel rate of 17.98 GPixel/s and a texture rate of 26.98 GTexel/s, while the M500M manages only 8.992 GPixel/s and 17.98 GTexel/s. Both cards deliver the same FP32 performance at 863.2 GFLOPS, which means compute-heavy shader workloads may scale similarly, but memory bandwidth and fill-rate-limited tasks will favor the K620 decisively.

Clock speeds are nearly identical: the K620 runs at 1058 MHz base and 1124 MHz boost, while the M500M runs at 1029 MHz base and the same 1124 MHz boost. The K620’s slightly higher base clock contributes marginally to its edge, but the architectural differences in memory bus and ROP count are far more impactful. Power consumption reflects the design goals: the K620 has a 45 W TDP, while the M500M draws only 30 W. The K620 is a single-slot card with no power connectors, while the M500M is an MXM Module with a 3.0 interface. Display outputs also diverge: the K620 offers 1x DVI and 1x DisplayPort 1.2, whereas the M500M’s outputs are portable-device dependent, meaning they vary by laptop implementation.

Both cards support DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.4, so API compatibility is not a differentiator. The K620 is listed as a Quadro Kepler (Kx200) generation part released on July 21, 2014, with a predecessor of Quadro Fermi and successor of Quadro Maxwell. The M500M is a Quadro Maxwell-M (Mx000M) part released on April 26, 2016, with a predecessor of Quadro Kepler-M and successor of Quadro Pascal-M. Despite the M500M’s later release, its smaller chip and reduced memory bus place it below the K620 in measured performance.

The Verdict

The data points to a single conclusion: the NVIDIA Quadro K620 is the stronger GPU in every recorded benchmark. It wins both head-to-head tests, holds a higher average benchmark score, and sits in a higher percentile of all GPUs. For users who already have a desktop workstation with a PCIe 2.0 x16 slot, the K620 offers superior memory bandwidth, double the pixel rate, and a 12% lead in Vulkan performance over the M500M.

The M500M is not without merit. Its 30 W TDP makes it far more power-efficient, which is essential for mobile workstations. The identical FP32 throughput (863.2 GFLOPS) means that pure compute workloads, such as certain OpenCL kernels, may see similar raw math performance. However, the M500M’s 64-bit memory bus and halved ROP count will bottleneck any task that touches memory frequently. The benchmark results confirm this: the M500M trails by 11.8% in OpenCL and 12.4% in Vulkan, a consistent pattern across both APIs.

The choice is straightforward. For a desktop workstation where power draw is not a primary constraint, the K620 is the better pick. Its higher bandwidth and fill rates translate directly into measurable performance gains. For a laptop or compact mobile system, the M500M is the only viable option given its MXM form factor, but the recorded data shows a clear performance sacrifice. The K620’s percentile placement at 36 versus the M500M’s 32 reinforces this hierarchy, and its rival list includes far more recent parts, indicating it remains competitive despite its 2014 release.

FAQ

Q: Which GPU has a higher average benchmark score?

A: The NVIDIA Quadro K620 averages 6282, while the NVIDIA Quadro M500M averages 5604.

Q: How much faster is the K620 in OpenCL?

A: The K620 scores 6693 in Geekbench OpenCL, which is 11.8% higher than the M500M’s 5986.

Q: Do both cards have the same amount of memory?

A: Yes, both have 2 GB of DDR3 memory, but the K620 uses a 128-bit bus while the M500M uses a 64-bit bus, giving the K620 28.80 GB/s versus 14.40 GB/s.

Q: Are there any workloads where the M500M matches the K620?

A: Both cards deliver identical FP32 performance at 863.2 GFLOPS, so raw compute shader math is the same, but memory-bound tasks will favor the K620.

Q: What is the power draw difference?

A: The K620 has a 45 W TDP, while the M500M consumes only 30 W, making the M500M the more power-efficient option.

Q: Which card supports newer graphics APIs?

A: Both support DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.4, so API support is identical.

Where Each One Wins

The NVIDIA Quadro K620 wins in every scenario where memory bandwidth, pixel throughput, or texture rate matters. Its 28.80 GB/s bandwidth is double the M500M’s, and its 17.98 GPixel/s pixel rate is exactly twice the M500M’s. This makes the K620 the clear choice for tasks like high-resolution rendering, multi-display output, or any OpenCL/Vulkan workload that streams large datasets. The benchmark data confirms this: the K620 leads by 11.8% in OpenCL and 12.4% in Vulkan, both substantial margins.

The NVIDIA Quadro M500M wins only in power efficiency and form factor suitability. Its 30 W TDP is a third lower than the K620’s 45 W, which matters in thermally constrained laptop chassis. The MXM Module design means it is the only one of the two that can be integrated into a portable workstation. For users who must have mobile GPU acceleration and cannot afford the power budget of a desktop card, the M500M is the practical choice, even though its scores are lower. The M500M’s identical FP32 throughput (863.2 GFLOPS) means it can still handle compute-heavy shader workloads, but the memory bus bottleneck will cap real-world performance.

The recorded data does not show a single test where the M500M wins. However, the use-case split is clear: the K620 for desktop compute and rendering, the M500M for mobility and low-power deployments. In a static workstation, there is no argument for the M500M based on benchmarks alone. In a mobile environment, the M500M’s lower power draw and MXM form factor are decisive, and its performance, while lower, remains functional for entry-level professional tasks. The K620’s 36th percentile ranking versus the M500M’s 32nd percentile underscores the overall gap, but the M500M’s niche is defined by physical constraints, not raw speed.