NVIDIA Quadro GV100 vs NVIDIA Quadro M6000 Comparison

Where Each One Wins

The benchmark data presents a starkly one-sided picture. The NVIDIA Quadro GV100 wins both recorded head-to-head tests outright, leaving the Quadro M6000 without a single victory in the database’s comparison set. This does not mean the M6000 is without merit, but its strengths lie in a different performance arena than the GV100.

The Quadro M6000, built on the Maxwell 2.0 architecture, shows its competitive edge in the Geekbench Vulkan test relative to its own average. Its Vulkan score of 46,913 is notably higher than its OpenCL score of 39,688, suggesting a platform-specific optimization or an architecture that handles Vulkan’s low-level overhead efficiently. For users whose workflows rely heavily on Vulkan-based applications, the M6000 punches above its weight class compared to its overall standing.

The Quadro GV100, by contrast, dominates in raw compute throughput. Its Geekbench OpenCL score of 150,004 is nearly four times the M6000’s result, indicating a massive advantage in general-purpose GPU compute tasks that leverage OpenCL. The GV100 also leads in Vulkan with 139,526 points, though the margin there is smaller in percentage terms. The data clearly positions the GV100 as the compute powerhouse, while the M6000 serves as a capable, more modest performer in API-specific workloads.

When looking at the database’s broader metrics, the M6000 actually holds a higher percentile ranking at 84 versus the GV100’s 80. This is a curious inversion: despite losing both head-to-head tests, the M6000 ranks better against all GPUs in the database. This suggests the M6000’s average benchmark score of 43,301 benefits from a wider range of tests where it performs relatively well, while the GV100’s average of 35,520 is dragged down by poor results in certain legacy DirectX tests, such as its Passmark DirectX 12 score of just 84. The GV100 wins where it matters for modern compute, but the M6000 shows more consistency across a broader benchmark suite.

Architecture Differences

The architectural gap between these two cards is profound, reflecting a generational leap in design philosophy. The Quadro M6000 uses the GM200 chip on a 28 nm process from TSMC, packing 8,000 million transistors onto a 601 mm² die. The Quadro GV100 uses the GV100 chip on a 12 nm process, also from TSMC, with 21,100 million transistors on an 815 mm² die. This represents a 2.6x increase in transistor count and a 2.5x increase in die area, with transistor density jumping from 13.3 million per mm² on the M6000 to 25.9 million per mm² on the GV100.

Clock speeds tell a similar story of progression. The M6000 runs at a base of 988 MHz with a boost of 1114 MHz, while the GV100 runs at 1132 MHz base and 1627 MHz boost. The GV100’s boost clock is nearly 46% higher than the M6000’s, a substantial advantage that compounds with its larger core configuration. The memory subsystem differs even more dramatically. The M6000 uses 12 GB of GDDR5 on a 384-bit bus, delivering 317.4 GB/s of bandwidth. The GV100 uses 32 GB of HBM2 on a massive 4096-bit bus, yielding 868.4 GB/s of bandwidth, a 2.7x improvement. Memory clock speeds are not directly comparable due to different memory types, but the effective bandwidth difference is the key metric.

Core counts scale accordingly. The M6000 has 3,072 shading units, 192 texture mapping units, and 96 ROPs. The GV100 has 5,120 shading units, 320 TMUs, and 128 ROPs. The GV100 also introduces 640 tensor cores, a feature entirely absent from the M6000. These tensor cores are designed for deep learning and AI workloads, giving the GV100 a specialized capability the M6000 cannot match. Pixel rate increases from 106.9 GPixel/s on the M6000 to 208.3 GPixel/s on the GV100, and texture rate jumps from 213.9 GTexel/s to 520.6 GTexel/s.

FP32 compute offers a clear hierarchy: the M6000 delivers 6.844 TFLOPS, while the GV100 delivers 16.66 TFLOPS, a 2.4x advantage. The GV100 also provides FP16 performance of 33.32 TFLOPS at a 2:1 ratio, a feature the M6000 lacks entirely. Both cards share the same TDP of 250 W, dual-slot width, single 8-pin power connector, 600 W suggested PSU, and PCIe 3.0 x16 interface. Physical dimensions are identical at 267 mm length and 111 mm height. Display outputs differ: the M6000 offers 1x DVI and 4x DisplayPort 1.2, while the GV100 offers 4x DisplayPort 1.4a. Both support DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4.

Head-to-Head Benchmarks

The database records two direct comparisons between these cards, and the GV100 wins both by decisive margins. In Geekbench OpenCL, the GV100 scores 150,004 against the M6000’s 39,688, a delta of -73.5% from the GV100’s perspective. This means the GV100 outperforms the M6000 by roughly 278% in raw OpenCL compute. This is the single largest victory in the head-to-head set and reflects the GV100’s superior core count, higher clocks, and vastly larger memory bandwidth.

In Geekbench Vulkan, the GV100 scores 139,526 against the M6000’s 46,913, a delta of -66.4%. The absolute gap is smaller than in OpenCL, but the GV100 still leads by nearly 197%. The M6000’s Vulkan score is its stronger result, yet it remains far behind the GV100. The data indicates that the GV100’s architectural advantages translate across both major GPU compute APIs, not just one.

Looking at the GV100’s broader benchmark profile, its Passmark results reveal an interesting split. It scores 19,650 in Passmark G3D and 9,069 in Passmark GPU Compute, but its DirectX-specific scores are low: 140 in DirectX 10, 168 in DirectX 11, 84 in DirectX 12, and 207 in DirectX 9. The 2D score of 836 is modest. These low DirectX numbers likely explain why the GV100’s average benchmark score of 35,520 sits below the M6000’s 43,301, despite the GV100 winning the head-to-head tests. The M6000 has no Passmark scores recorded in the database, so its average is derived solely from the two Geekbench tests.

The nearest rival data provides context for each card’s standing. The M6000’s closest competitor is the NVIDIA GeForce RTX 5050 Mobile with an average score of 43,268, a delta of just 0.1%. The Quadro M6000 24 GB variant is nearly identical at 43,262, also 0.1% away. The GeForce RTX 4070 SUPER sits at 43,223, 0.2% behind, while the GeForce RTX 4090 Mobile leads the M6000 by 0.8% with a score of 43,667. These tiny deltas indicate the M6000 is positioned in a highly competitive cluster of GPUs.

The GV100’s rivals show a different pattern. The NVIDIA GeForce RTX 5070 Ti Mobile scores 35,435, just 0.2% behind the GV100. The AMD Radeon Pro Duo scores 35,860, leading the GV100 by 0.9%. The NVIDIA T1000 scores 36,289, leading by 2.1%, while the NVIDIA A2 scores 34,690, trailing by 2.4%. The GV100’s average is thus surrounded by a mix of mobile and workstation parts, reflecting its niche positioning.

The Verdict

The data points to a clear conclusion: the NVIDIA Quadro GV100 is the superior card for compute-intensive workloads, while the Quadro M6000 holds its own in a narrower set of conditions. Users who prioritize OpenCL or Vulkan performance should choose the GV100 without hesitation. Its 150,004 OpenCL score and 139,526 Vulkan score dwarf the M6000’s 39,688 and 46,913 respectively. The GV100 also offers 32 GB of HBM2 memory versus 12 GB of GDDR5, a 2.7x bandwidth advantage, and tensor cores for AI tasks. Its FP32 output of 16.66 TFLOPS is 2.4x the M6000’s 6.844 TFLOPS, and its FP16 capability at 33.32 TFLOPS is absent on the M6000.

However, the M6000 is not without a case. Its percentile ranking of 84 versus the GV100’s 80 suggests it performs more consistently across the full range of database tests. Its average benchmark score of 43,301 exceeds the GV100’s 35,520, driven by the GV100’s weak Passmark DirectX results. For users running legacy DirectX applications, the GV100’s scores of 84 to 207 in those tests are concerning, while the M6000’s absence of such low results implies better suitability for older workloads. The M6000 also sits within 0.8% of the GeForce RTX 4090 Mobile, a modern high-end part, indicating its Maxwell architecture remains competitive in certain metrics.

The choice depends on workload profile. For modern compute, AI, and high-bandwidth tasks, the GV100 is the clear winner. For legacy API compatibility and broader benchmark consistency, the M6000 offers a more balanced profile. The GV100’s launch MSRP is 8,999 USD, reflecting its workstation positioning, while the M6000 has no recorded launch price. Both cards are end-of-life, but the GV100’s architectural advantages make it the more future-proof option for users who can tolerate its poor DirectX performance.

FAQ

Q: Which card has higher OpenCL performance?

A: The Quadro GV100 scores 150,004 in Geekbench OpenCL, while the Quadro M6000 scores 39,688. The GV100 leads by 73.5% in delta terms, representing roughly a 278% advantage in raw score.

Q: How do the cards compare in Vulkan benchmarks?

A: The GV100 scores 139,526 in Geekbench Vulkan versus the M6000’s 46,913. The GV100 wins by a 66.4% delta, which translates to approximately 197% higher performance.

Q: What is the memory capacity difference?

A: The Quadro M6000 has 12 GB of GDDR5 memory on a 384-bit bus with 317.4 GB/s bandwidth. The Quadro GV100 has 32 GB of HBM2 memory on a 4096-bit bus with 868.4 GB/s bandwidth.

Q: Does the GV100 support tensor cores?

A: Yes, the GV100 includes 640 tensor cores, a feature the M6000 lacks entirely. These are designed for deep learning and AI workloads.

Q: Why does the M6000 have a higher percentile ranking despite losing both head-to-head tests?

A: The M6000 ranks in the 84th percentile versus the GV100’s 80th. Its average benchmark score of 43,301 exceeds the GV100’s 35,520 because the GV100 posts very low Passmark DirectX scores, including 84 in DirectX 12 and 140 in DirectX 10, which drag down its average.

Q: What are the FP32 compute differences?

A: The M6000 delivers 6.844 TFLOPS of FP32 performance, while the GV100 delivers 16.66 TFLOPS. The GV100 also offers 33.32 TFLOPS of FP16 at a 2:1 ratio, which the M6000 does not provide.