NVIDIA Quadro GV100 vs NVIDIA Quadro M6000 24 GB Comparison

Head-to-Head Benchmarks

The recorded data set contains two direct benchmark comparisons between the NVIDIA Quadro M6000 24 GB and the NVIDIA Quadro GV100. In both cases, the GV100 emerges as the decisive winner, with the M6000 trailing by substantial margins. The most striking result is in the Geekbench OpenCL test, where the GV100 scores 150,004 points against the M6000's 40,098 points. This represents a delta of -73.3% for the M6000, meaning the GV100 delivers roughly 3.7 times the compute throughput in this workload. The OpenCL benchmark is particularly relevant for professional users because it exercises general-purpose GPU compute, a core function for rendering, simulation, and data processing tasks.

The second head-to-head test, Geekbench Vulkan, shows a similar pattern. The GV100 records 139,526 points, while the M6000 manages 46,425 points, a delta of -66.7%. Vulkan is a low-level graphics API, and the GV100's advantage here indicates not only superior raw compute but also more efficient handling of modern graphics workloads. The M6000, built on the older Maxwell architecture, simply cannot keep pace with the Volta-based GV100 in these API-level benchmarks. Across the two recorded tests, the GV100 wins both, giving it a clean 2-0 record in head-to-head competition.

Contextualizing these scores against the broader database, the M6000 24 GB holds an average benchmark score of 43,262 and sits at the 83rd percentile among all GPUs. Its nearest rivals include the NVIDIA GeForce RTX 5050 Mobile (average score 43,268, delta 0%), the NVIDIA Quadro M6000 (43,301, delta -0.1%), the NVIDIA GeForce RTX 4070 SUPER (43,223, delta 0.1%), and the NVIDIA GeForce RTX 4090 Mobile (43,667, delta -0.9%). These deltas are all within a single percentage point, indicating that the M6000 24 GB performs essentially at parity with these modern consumer and mobile parts in aggregate benchmark terms. The M6000 24 GB's individual OpenCL score of 40,098 is below its own average, while its Vulkan score of 46,425 pulls the average upward.

The GV100, by contrast, has an average benchmark score of 35,520 and sits at the 80th percentile. Its nearest rivals include the NVIDIA GeForce RTX 5070 Ti Mobile (35,435, delta 0.2%), the AMD Radeon Pro Duo (35,860, delta -0.9%), the NVIDIA T1000 (36,289, delta -2.1%), and the NVIDIA A2 (34,690, delta 2.4%). The GV100's average is dragged down by its Passmark results, which are notably weak: DirectX 10 scores 140, DirectX 11 scores 168, DirectX 12 scores 84, DirectX 9 scores 207, G2D scores 836, G3D scores 19,650, and GPU compute scores 9,069. These low DirectX scores likely reflect the GV100's professional focus rather than gaming capability, but they still contribute to its aggregate average. The GV100's two Geekbench scores, however, are exceptional: 150,004 in OpenCL and 139,526 in Vulkan, both far exceeding its average and its rivals.

The delta between the two cards in head-to-head testing is stark. In OpenCL, the GV100 leads by 109,906 points, and in Vulkan, by 93,101 points. These are not marginal differences; they represent fundamental architectural generation gaps. The M6000's best individual score, 46,425 in Vulkan, is still less than one-third of the GV100's Vulkan result. Even the M6000's average benchmark score of 43,262 falls short of the GV100's lowest Geekbench score by a wide margin. The data clearly indicates that the GV100 is in a different performance class for compute and modern graphics API workloads.

FAQ

Q: Which card wins the head-to-head benchmark comparisons?

A: The NVIDIA Quadro GV100 wins both recorded tests. It scores 150,004 in Geekbench OpenCL versus 40,098 for the M6000 24 GB, and 139,526 in Geekbench Vulkan versus 46,425 for the M6000 24 GB.

Q: How large is the performance gap in the OpenCL test?

A: The M6000 24 GB trails by 73.3% in Geekbench OpenCL. The GV100's score of 150,004 is approximately 3.7 times the M6000's 40,098.

Q: What is the average benchmark score for each card?

A: The NVIDIA Quadro M6000 24 GB has an average benchmark score of 43,262. The NVIDIA Quadro GV100 has an average benchmark score of 35,520.

Q: How do the cards compare to their nearest rivals in the database?

A: The M6000 24 GB is within 0.9% of its nearest rivals, including the GeForce RTX 5050 Mobile (delta 0%), the Quadro M6000 (delta -0.1%), the GeForce RTX 4070 SUPER (delta 0.1%), and the GeForce RTX 4090 Mobile (delta -0.9%). The GV100 is within 2.4% of its rivals, including the GeForce RTX 5070 Ti Mobile (delta 0.2%), the Radeon Pro Duo (delta -0.9%), the T1000 (delta -2.1%), and the A2 (delta 2.4%).

Q: What percentile ranking does each card hold?

A: The M6000 24 GB sits at the 83rd percentile among all GPUs, while the GV100 sits at the 80th percentile.

Q: Does the GV100 have any weak benchmark results?

A: Yes, the GV100 records low Passmark DirectX scores, including 140 in DirectX 10, 168 in DirectX 11, 84 in DirectX 12, and 207 in DirectX 9. Its Passmark G2D score is 836, G3D is 19,650, and GPU compute is 9,069.

The Verdict

The data points to a clear division of roles. For users whose workloads emphasize OpenCL compute or Vulkan-based rendering, the NVIDIA Quadro GV100 is the overwhelming choice. Its 150,004 OpenCL score and 139,526 Vulkan score dwarf the M6000 24 GB's corresponding results of 40,098 and 46,425. The GV100's 640 tensor cores and Volta architecture provide capabilities that the M6000 24 GB simply cannot match, as evidenced by the 73.3% and 66.7% deltas in the two head-to-head tests.

However, the GV100's aggregate benchmark profile is uneven. Its Passmark DirectX scores are remarkably low, with the DirectX 12 result at just 84 points. This suggests that the GV100 is not optimized for traditional DirectX gaming workloads, and users prioritizing those tasks should look elsewhere. The M6000 24 GB, while trailing in compute, holds a higher percentile ranking at 83 versus the GV100's 80, and its average benchmark score of 43,262 is actually higher than the GV100's 35,520, largely because the M6000 does not suffer from the GV100's weak DirectX results.

For professional users focused on compute-intensive tasks like scientific simulation, machine learning inference, or large-scale rendering with OpenCL, the GV100 is the data-backed pick. Its Geekbench scores are in a different league. For users with mixed workloads that include DirectX applications, the M6000 24 GB offers a more balanced profile, though it remains a last-generation product. The M6000 24 GB's nearest rivals, such as the GeForce RTX 4070 SUPER and RTX 4090 Mobile, all sit within 0.9% of its average score, indicating that it remains competitive with modern parts in aggregate terms. The GV100's rivals, including the RTX 5070 Ti Mobile and the Radeon Pro Duo, are similarly close, with deltas under 2.5%.

Specification Differences

The two cards differ across nearly every major specification category. The M6000 24 GB uses a 28 nm process node, while the GV100 uses a 12 nm node. Transistor count jumps from 8,000 million on the M6000 to 21,100 million on the GV100, and die size grows from 601 mm² to 815 mm². Transistor density increases from 13.3M per mm² to 25.9M per mm². Clock speeds differ substantially: the M6000 has a base clock of 988 MHz and a boost of 1114 MHz, while the GV100 runs at 1132 MHz base and 1627 MHz boost. Memory configurations are entirely different: the M6000 uses 24 GB of GDDR5 on a 384-bit bus with 317.4 GB/s bandwidth, while the GV100 uses 32 GB of HBM2 on a 4096-bit bus with 868.4 GB/s bandwidth. Memory clock rates are 1653 MHz (6.6 Gbps effective) for the M6000 versus 848 MHz (1696 Mbps effective) for the GV100.

Compute resources differ markedly. The M6000 has 3,072 shading units, 192 TMUs, and 96 ROPs, while the GV100 has 5,120 shading units, 320 TMUs, and 128 ROPs. The GV100 also includes 640 tensor cores, a feature entirely absent from the M6000. Pixel rate rises from 106.9 GPixel/s to 208.3 GPixel/s, and texture rate from 213.9 GTexel/s to 520.6 GTexel/s. FP32 throughput increases from 6.844 TFLOPS to 16.66 TFLOPS. The GV100 also offers FP16 performance of 33.32 TFLOPS (2:1), while the M6000 has no recorded FP16 figure. Display outputs differ as well: the M6000 provides 1x DVI and 4x DisplayPort 1.2, while the GV100 provides 4x DisplayPort 1.4a. Launch MSRP is 4,999 USD for the M6000 and 8,999 USD for the GV100. Release dates are 2016-03-04 for the M6000 and 2018-03-26 for the GV100.

Architecture Differences

The architectural divide is fundamental. The M6000 24 GB is built on Maxwell 2.0, using the GM200 chip, while the GV100 uses Volta architecture with the GV100 chip. These represent two distinct generations: the M6000 belongs to the Quadro Maxwell (Mx000) generation, and the GV100 belongs to the Quadro Volta (Vx000) generation. The M6000's predecessor is Quadro Kepler, and its successor is Quadro Pascal. The GV100's predecessor is Quadro Pascal, and its successor is Quadro Turing. This places the two cards on opposite sides of the Pascal generation, with the GV100 being two architectural generations ahead of the M6000.

The process technology difference is significant: 28 nm for the M6000 versus 12 nm for the GV100, both fabricated by TSMC. This node shrink, combined with a much larger die (815 mm² versus 601 mm²), allows the GV100 to pack 21,100 million transistors versus 8,000 million, more than doubling the transistor count. The transistor density figure of 25.9M per mm² for the GV100 versus 13.3M per mm² for the M6000 reflects the combined benefits of the smaller node and architectural improvements.

The most notable architectural addition on the GV100 is its 640 tensor cores, which are designed for matrix operations and deep learning workloads. The M6000 has no tensor cores. Both cards share identical API support for DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. Both use PCIe 3.0 x16 interfaces, have a TDP of 250 W, are dual-slot cards, use a single 8-pin power connector, and recommend a 600 W power supply. Physical dimensions are identical at 267 mm length and 111 mm height. Both cards are end-of-life products, but their architectural trajectories are very different: Maxwell 2.0 was optimized for the mid-2010s, while Volta introduced features like tensor cores that have become industry standards for AI acceleration. The benchmark data reflects this gap, with the GV100's compute scores far exceeding the M6000's, despite the M6000 holding a slightly higher percentile ranking due to its more consistent benchmark profile.