NVIDIA Quadro 6000 vs NVIDIA Quadro K5100M Comparison

The NVIDIA Quadro K5100M and NVIDIA Quadro 6000 represent two distinct generations of professional mobile and desktop computing, separated by nearly three years of architectural evolution. The K5100M, built on the Kepler architecture, enters with a 48th percentile ranking against all GPUs, while the Quadro 6000, a Fermi-era card, sits just one percentile lower at 47. Despite their similar overall standing, the benchmark data reveals a decisive performance gap, with the K5100M achieving an average benchmark score of 10,043 compared to the Quadro 6000’s 9,846. This places the K5100M approximately 2% ahead of its older counterpart, a margin that widens significantly in specific workloads. The head-to-head comparison shows the K5100M winning the sole shared benchmark by 19.6%, indicating that architectural improvements translate into substantial real-world advantages.

Where Each One Wins

The performance landscape between these two Quadro cards is not a matter of different strengths, but rather a question of generational superiority. The K5100M wins the only directly comparable benchmark, the Geekbench OpenCL test, with a score of 11,771 against the Quadro 6000’s 9,846. This 19.6% advantage means the K5100M is unequivocally faster in compute-heavy tasks that leverage OpenCL. The K5100M also holds a lead in the Geekbench Metal test, scoring 8,315, a test the Quadro 6000 does not even participate in due to its lack of Metal API support. In practical terms, this means the K5100M is the better choice for any modern professional workload that utilizes GPU compute, including rendering, simulation, and data processing.

The Quadro 6000, however, does have its own domain where it can claim a theoretical edge: memory bandwidth. With a 384-bit memory bus and 143.4 GB/s of bandwidth, it outpaces the K5100M’s 256-bit bus and 115.2 GB/s. This could theoretically benefit workloads that are heavily memory-bandwidth bound, such as certain types of large texture streaming or specific scientific computations. Yet, the benchmark data suggests that this bandwidth advantage does not translate into a practical win. The K5100M’s superior compute throughput and higher clock speeds compensate for its narrower bus, resulting in an overall faster experience. In the single head-to-head test, the Quadro 6000 fails to secure a single win, making the K5100M the clear victor across all measured metrics.

Architecture Differences

The fundamental differences between these two cards stem from their underlying architectures. The K5100M is built on the Kepler architecture, utilizing the GK104 chip manufactured on a 28 nm process at TSMC. This process node is significantly more advanced than the Quadro 6000’s 40 nm process, which uses the GF100 Fermi chip. The smaller process node allows the K5100M to pack 3,540 million transistors into a 294 mm² die, achieving a transistor density of 12.0 million per square millimeter. In contrast, the Quadro 6000’s 3,100 million transistors are spread across a much larger 529 mm² die, resulting in a density of only 5.9 million per square millimeter. This makes the K5100M a more efficient design, both in terms of power and space.

The core configurations diverge dramatically. The K5100M features 1,536 shading units, 128 texture mapping units (TMUs), and 32 raster operation units (ROPs). The Quadro 6000, by contrast, contains only 448 shading units, 56 TMUs, and 48 ROPs. This means the K5100M has over three times the shading units and more than double the TMUs, which directly contributes to its higher fill rates. The K5100M achieves a pixel rate of 24.67 GPixel/s and a texture rate of 98.69 GTexel/s, while the Quadro 6000 manages only 16.07 GPixel/s and 32.14 GTexel/s, respectively. The K5100M’s floating-point performance is also superior, delivering 2.369 TFLOPS compared to the Quadro 6000’s 1,027.7 GFLOPS.

Memory configurations also differ, with the K5100M offering 8 GB of GDDR5 memory on a 256-bit bus, while the Quadro 6000 provides 6 GB on a wider 384-bit bus. The effective memory clock differs as well, with the K5100M running at 3.6 Gbps effective versus the Quadro 6000’s 3 Gbps effective. This results in the Quadro 6000 having higher peak bandwidth (143.4 GB/s) but less overall capacity. The K5100M is also more power-efficient, with a TDP of 100 W compared to the Quadro 6000’s 204 W. The form factors reflect their intended uses: the K5100M is an MXM module for laptops, while the Quadro 6000 is a dual-slot desktop card requiring a 550 W power supply.

Head-to-Head Benchmarks

The only direct comparison available is the Geekbench OpenCL test, and the results are stark. The K5100M scores 11,771, while the Quadro 6000 scores 9,846. This represents a 19.6% advantage for the K5100M, a substantial margin that underscores the generational leap in compute performance. This single result is telling because OpenCL is a cross-platform, vendor-neutral API that stresses raw compute throughput, memory access, and shader execution. The K5100M’s superior shading unit count and higher clock speeds allow it to process parallel workloads far more efficiently than the Fermi-based Quadro 6000.

Looking at the broader benchmark context, the K5100M also has a Geekbench Metal score of 8,315, a test that the Quadro 6000 cannot run due to its lack of Vulkan and Metal API support. This absence further limits the Quadro 6000’s relevance in modern software environments. The average benchmark scores reinforce the trend: the K5100M averages 10,043, placing it just 0.3% behind the AMD Radeon R9 M375 and 0.8% ahead of the NVIDIA GeForce GTX 870M. The Quadro 6000, with an average of 9,846, sits 0.1% ahead of the NVIDIA Quadro M2000M and 1.1% behind the same GeForce GTX 870M. These rival comparisons show that the K5100M is competitive with mid-range mobile GPUs of its era, while the Quadro 6000 lags behind even older mobile parts.

The K5100M’s win count of 1 against the Quadro 6000’s 0 in head-to-head benchmarks is a clean sweep. There is no single test where the Quadro 6000 outperforms its successor. The 19.6% delta in OpenCL is the definitive data point, showing that the K5100M is not just incrementally faster, but significantly more capable in compute-intensive tasks. This is a clear case of generational improvement delivering measurable performance gains.

FAQ

Q: Which card is faster in the Geekbench OpenCL benchmark?

A: The NVIDIA Quadro K5100M is faster, scoring 11,771 compared to the Quadro 6000’s 9,846, a 19.6% difference in favor of the K5100M.

Q: Does the Quadro 6000 have any benchmark win over the K5100M?

A: No. In the sole head-to-head benchmark, the K5100M wins 1–0. The Quadro 6000 does not win any of the direct comparisons.

Q: What is the memory bandwidth of each card?

A: The Quadro 6000 has a higher memory bandwidth of 143.4 GB/s due to its 384-bit bus, while the K5100M has 115.2 GB/s from a 256-bit bus.

Q: Are both cards compatible with Vulkan?

A: No. The K5100M supports Vulkan version 1.2.175, but the Quadro 6000 has no Vulkan support listed.

Q: How do their average benchmark scores compare to the GeForce GTX 870M?

A: The K5100M is 0.8% ahead of the GTX 870M, while the Quadro 6000 is 1.1% behind it.

Q: What is the TDP difference between the two cards?

A: The K5100M has a TDP of 100 W, whereas the Quadro 6000 has a significantly higher TDP of 204 W.

The Verdict

The data is unequivocal: the NVIDIA Quadro K5100M is the superior GPU. It outperforms the Quadro 6000 by 19.6% in the only shared benchmark, has over three times the shading units, and delivers more than double the floating-point performance. For any professional seeking maximum compute throughput in rendering, simulation, or data analysis, the K5100M is the clear choice. Its higher average benchmark score of 10,043 versus 9,846 places it in a higher performance tier, and its support for modern APIs like Vulkan ensures greater software compatibility.

The Quadro 6000’s only advantages are its wider memory bus and higher bandwidth, but these do not manifest in any benchmark victory. Its 6 GB of memory is also less than the K5100M’s 8 GB, though the Quadro 6000 does offer a larger physical footprint and a dual-slot design for desktop workstations. The Quadro 6000 was launched with a launch MSRP of 4,399 USD, but this does not offset its performance deficit. For users with legacy software that specifically relies on Fermi-era quirks, the Quadro 6000 might still function, but it is objectively slower and less efficient. The K5100M wins on performance, power efficiency, and modern feature support, making it the only rational recommendation from this data.