NVIDIA Quadro M4000M vs NVIDIA Tesla K20m Comparison

The NVIDIA Quadro M4000M and NVIDIA Tesla K20m are both end-of-life professional GPUs from NVIDIA, but they target entirely different segments of the market. The Quadro M4000M is a mobile workstation part built on the Maxwell 2.0 architecture, while the Tesla K20m is a dual-slot compute accelerator based on the older Kepler architecture. Benchmark data shows a near-even split in performance wins, but their underlying designs reveal distinct strengths that cater to different workloads.

FAQ

Q: Which GPU has the higher average benchmark score?

A: The NVIDIA Quadro M4000M has a higher average benchmark score of 20,480, compared to the NVIDIA Tesla K20m’s average of 19,089. This places the Quadro M4000M in the 65th percentile of all GPUs, while the Tesla K20m sits just behind in the 64th percentile.

Q: How do the two GPUs compare in OpenCL performance?

A: The Quadro M4000M wins the Geekbench OpenCL test with a score of 19,989, which is 23.1% higher than the Tesla K20m’s score of 16,241. This is a significant margin in favor of the mobile workstation card.

Q: Which GPU performs better in Vulkan?

A: The Tesla K20m takes the Vulkan test with a score of 21,936, beating the Quadro M4000M’s score of 20,971 by 4.4%. This shows the older Kepler card still has an edge in this particular API workload.

Q: What are the core specifications of each GPU?

A: The Quadro M4000M features 1,280 shading units, 80 texture mapping units, and 64 ROPs, running on a 256-bit memory bus with 4 GB of GDDR5. The Tesla K20m has 2,496 shading units, 208 TMUs, and 40 ROPs, with a 320-bit bus and 5 GB of GDDR5 memory.

Q: What is the power consumption difference between the two?

A: The Quadro M4000M has a TDP of 100 W and uses an MXM Module slot width with no power connectors. The Tesla K20m has a much higher TDP of 225 W, requires a dual-slot form factor, and needs both a 6-pin and an 8-pin power connector, with a suggested PSU of 550 W.

Q: Which GPU supports newer API versions?

A: The Quadro M4000M supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. The Tesla K20m supports DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.2.175, meaning the Quadro has an advantage in both DirectX feature level and Vulkan version.

Where Each One Wins

The Quadro M4000M is the clear winner in OpenCL compute tasks, posting a score of 19,989 versus the Tesla K20m’s 16,241 — a 23.1% advantage. This makes it the better choice for applications that rely heavily on OpenCL acceleration, such as certain rendering engines, video processing tools, and scientific simulation software. Its higher pixel rate of 64.83 GPixel/s, compared to the Tesla’s 36.71 GPixel/s, also suggests it handles rasterization and display-oriented workloads more efficiently, which aligns with its role as a mobile workstation GPU.

The Tesla K20m, on the other hand, wins in the Vulkan benchmark with a score of 21,936, beating the Quadro’s 20,971 by 4.4%. It also offers substantially higher raw compute throughput in terms of texture rate (146.8 GTexel/s vs. 81.04 GTexel/s) and FP32 performance (3.524 TFLOPS vs. 2.593 TFLOPS). These specifications point to strengths in compute-heavy tasks that can leverage its larger number of shading units and wider memory bus, particularly in environments where Vulkan is the primary API.

Architecture Differences

The two GPUs come from different architectural generations. The Quadro M4000M is built on Maxwell 2.0, using the GM204 chip with 5,200 million transistors on a 398 mm² die. The Tesla K20m uses the older Kepler architecture with the GK110 chip, packing 7,080 million transistors onto a larger 561 mm² die. Despite the Tesla having more transistors and a bigger die, the transistor density is slightly lower: 13.1M per mm² for the Maxwell chip versus 12.6M per mm² for the Kepler chip.

The shading unit configuration differs dramatically. The Tesla K20m has 2,496 shading units and 208 TMUs, while the Quadro M4000M has 1,280 shading units and 80 TMUs. However, the Quadro has more ROPs (64 vs. 40), which explains its higher pixel fill rate. The Tesla’s higher texture rate comes from having more than double the TMUs. Both GPUs lack dedicated ray tracing and tensor cores, as those features came later in NVIDIA’s lineup.

The memory subsystems also reflect different design goals. The Tesla K20m has 5 GB of GDDR5 on a 320-bit bus, delivering 208.0 GB/s of bandwidth. The Quadro M4000M has 4 GB on a 256-bit bus, providing 160.4 GB/s. The Tesla’s wider bus and higher memory clock (1300 MHz vs. 1253 MHz) give it a bandwidth advantage that benefits large data transfers.

Specification Differences

The most obvious differences are in physical and power requirements. The Quadro M4000M is an MXM Module with no power connectors and a 100 W TDP, designed for laptops and mobile workstations. The Tesla K20m is a 267 mm (10.5 inch) dual-slot card requiring 1x 6-pin and 1x 8-pin power connectors, with a 225 W TDP and a suggested PSU of 550 W. The Quadro has display outputs that are portable-device dependent, while the Tesla has no display outputs at all.

The bus interfaces differ as well: the Quadro uses PCIe 3.0 x16, while the Tesla uses the older PCIe 2.0 x16. Clock speeds are only partially specified for the Quadro, with a base of 975 MHz and boost of 1013 MHz; the Tesla’s base and boost clocks are not provided in the data. Memory effective speed is 5 Gbps for the Quadro and 5.2 Gbps for the Tesla.

API support also separates them. The Quadro M4000M supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. The Tesla K20m supports DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.2.175. The Quadro’s newer architecture gives it a higher DirectX feature level and a more recent Vulkan version. The Tesla was released on 2013-01-04, while the Quadro came later on 2015-08-17.

Head-to-Head Benchmarks

The benchmark results are split one win each, with the Quadro M4000M taking the OpenCL test and the Tesla K20m taking the Vulkan test. The most dramatic difference is in OpenCL, where the Quadro scores 19,989 versus the Tesla’s 16,241, representing a 23.1% advantage for the Quadro. This is a substantial gap that makes the Quadro the better choice for OpenCL-based workloads.

The Vulkan test is much closer. The Tesla K20m scores 21,936, only 4.4% higher than the Quadro’s 20,971. While the Tesla wins this round, the margin is narrow, suggesting the two GPUs are more comparable in Vulkan performance. The raw compute specifications back this up: the Tesla has higher FP32 performance (3.524 TFLOPS vs. 2.593 TFLOPS) and texture rate (146.8 GTexel/s vs. 81.04 GTexel/s), but the Quadro counters with a higher pixel rate (64.83 GPixel/s vs. 36.71 GPixel/s).

Looking at the overall averages, the Quadro M4000M’s average benchmark score of 20,480 puts it ahead of the Tesla K20m’s 19,089. The Quadro’s nearest rivals include the NVIDIA GeForce RTX 3070 Mobile and Intel Arc B570, both within 0.5% of its score. The Tesla’s closest competitor is the NVIDIA GeForce GTX 780, which sits 0.4% above it, and the NVIDIA Quadro K6000, which is 0.3% below.

The Verdict

The data points to a clear split: choose the Quadro M4000M for OpenCL-heavy workloads and mobile workstation use, and choose the Tesla K20m for Vulkan-oriented compute tasks where raw shader throughput matters more. The Quadro’s 23.1% OpenCL lead is decisive, and its higher pixel rate makes it better suited for tasks that involve display output or rasterization. Its lower TDP of 100 W and MXM form factor also make it feasible for laptop integration.

The Tesla K20m, with its 2,496 shading units and 208 TMUs, is built for sheer compute density. Its Vulkan win of 4.4% is modest, but its FP32 performance of 3.524 TFLOPS and texture rate of 146.8 GTexel/s suggest it can handle heavy parallel workloads. However, its lack of display outputs and 225 W power draw limit it to dedicated compute servers or desktops with robust power supplies.

For most users, the Quadro M4000M is the more practical choice due to its higher average score, better OpenCL performance, and lower power requirements. The Tesla K20m remains relevant only for specific Vulkan-based compute tasks where its extra shading units can be fully utilized. The Quadro’s newer Maxwell 2.0 architecture also provides better API support, including Vulkan 1.4 versus the Tesla’s 1.2.175. Ultimately, the Quadro M4000M offers a more balanced profile, while the Tesla K20m is a specialized compute accelerator with a narrower focus.