NVIDIA Quadro M2000M vs NVIDIA Tesla M10 Comparison

# Head-to-Head Benchmarks

The benchmark data splits cleanly between these two Maxwell-based NVIDIA parts, with each card claiming one decisive victory in the two available tests. The NVIDIA Tesla M10 takes the Geekbench OpenCL test with a score of 10,318, beating the Quadro M2000M's 10,057 by 2.5%. That is a modest but real margin in raw compute throughput. The Quadro M2000M answers back in the Vulkan test, scoring 9,606 against the Tesla M10's 9,130 — a 5.2% advantage that is more than double the Tesla's OpenCL lead in percentage terms.

Looking at average benchmark scores, the two cards are effectively inseparable. The Quadro M2000M posts an average of 9,832, while the Tesla M10 averages 9,724. That 1.1% gap in the Quadro's favor falls well within run-to-run variance and places both cards in the same performance tier. Context from the nearest rivals confirms this: the Quadro M2000M sits 0.1% behind the NVIDIA Quadro 6000 (9,846), 0.3% ahead of the AMD FirePro W5000 (9,803), and 0.5% ahead of the NVIDIA GeForce GTX 1070 (9,780). The Tesla M10, meanwhile, is 0.1% ahead of the NVIDIA Tesla C2070 (9,716), 0.6% behind the GeForce GTX 1070, 0.6% ahead of the NVIDIA Quadro P4000 (9,665), and 0.7% ahead of the AMD Radeon Pro WX 2100 (9,653).

What the head-to-head numbers reveal is a split personality. The Tesla M10's higher OpenCL score suggests better raw compute execution, likely aided by its higher boost clock and memory clock. The Quadro M2000M's Vulkan win points to superior driver optimization or architectural efficiency in that specific API path. Neither card dominates the other outright — each wins exactly one benchmark, and the average scores land within 1.1% of each other. Both cards occupy the 47th percentile among all GPUs, which is a statistical tie. The data says these are peer products with different strengths depending on the workload API.

# Architecture Differences

Both cards are built on the same GM107 chip, which is the entry-level Maxwell die from TSMC's 28 nm process. The transistor count is identical at 1,870 million, and the die size matches at 148 mm², yielding the same transistor density of 12.6M per mm². This is the same silicon foundation, but the two cards are packaged and configured for very different purposes.

The Quadro M2000M is a mobile workstation part, using the MXM-A (3.0) bus interface and an MXM Module slot width. It draws 55 W and requires no external power connectors, making it a drop-in solution for professional laptops. The Tesla M10, by contrast, is a dual-slot server accelerator with a PCIe 3.0 x16 interface and a 225 W power draw that requires a single 8-pin power connector. The Tesla M10 is also 267 mm (10.5 inches) long, while the Quadro M2000M has no listed dimensions because it is designed for portable devices with form factors that vary by manufacturer.

The clock speeds tell an interesting story. The Quadro M2000M has a higher base clock at 1,098 MHz versus the Tesla M10's 1,033 MHz, but the Tesla M10 has a significantly higher boost clock at 1,306 MHz versus 1,137 MHz. That 169 MHz boost advantage is substantial and explains why the Tesla M10 can pull ahead in sustained compute workloads. The memory clocks also favor the Tesla M10: it runs at 1,300 MHz (5.2 Gbps effective) versus the Quadro M2000M's 1,253 MHz (5 Gbps effective). This translates into a bandwidth advantage of 83.20 GB/s versus 80.19 GB/s.

The memory capacity is a major differentiator. The Quadro M2000M comes with 4 GB of GDDR5 on a 128-bit bus, while the Tesla M10 doubles that to 8 GB on the same 128-bit bus. Both cards have 640 shading units, 40 texture mapping units, and 16 raster output units. Neither card has any ray tracing cores or tensor cores. The pixel rate favors the Tesla M10 at 20.90 GPixel/s versus 18.19 GPixel/s, and the texture rate also favors it at 52.24 GTexel/s versus 45.48 GTexel/s. The FP32 compute is listed as 1.672 TFLOPS for the Tesla M10 versus 1,455.4 GFLOPS for the Quadro M2000M, which is a roughly 15% advantage for the server card.

The API support is identical: both support DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.4. The display outputs differ fundamentally — the Quadro M2000M has portable-device-dependent outputs, while the Tesla M10 has no outputs at all, confirming its role as a headless compute accelerator. The production status for both is end-of-life. The Quadro M2000M was released on December 2, 2015, while the Tesla M10 followed on May 17, 2016.

# Where Each One Wins

The Quadro M2000M wins in the Vulkan API test, and that is its clearest area of superiority. A 5.2% lead in Vulkan over the Tesla M10 suggests that the mobile card handles modern graphics workloads with better efficiency, likely due to its lower power envelope and optimized mobile drivers. For users running Vulkan-based applications — which includes many modern game engines and compute frameworks — the Quadro M2000M is the better choice despite its lower raw clock speeds.

The Tesla M10 wins in OpenCL, posting a 2.5% higher score. This is the more common compute API for professional workloads such as rendering, scientific simulation, and machine learning inference. The Tesla M10's higher boost clock (1,306 MHz versus 1,137 MHz), higher memory clock (5.2 Gbps versus 5 Gbps), and higher bandwidth (83.20 GB/s versus 80.19 GB/s) all contribute to its OpenCL advantage. The doubling of memory from 4 GB to 8 GB also gives the Tesla M10 a significant capacity edge for datasets that exceed 4 GB, which is a common scenario in compute clusters.

For mobile workstation users, the Quadro M2000M's 55 W power draw and MXM form factor make it the only viable option between the two — the Tesla M10 cannot be installed in a laptop. For server deployments, the Tesla M10's PCIe interface, dual-slot design, and 225 W power envelope are standard, and its 8 GB memory capacity is a clear advantage for larger workloads. The Tesla M10 also has a higher pixel rate (20.90 GPixel/s versus 18.19 GPixel/s) and texture rate (52.24 GTexel/s versus 45.48 GTexel/s), which helps in compute-heavy graphics tasks that stress those units.

The average benchmark scores suggest that neither card has a systemic advantage. The Quadro M2000M's 9,832 average versus the Tesla M10's 9,724 is a 1.1% difference that could easily be noise. The real differentiators are the form factor, memory capacity, and API-specific performance. If your workload is Vulkan-heavy and mobile, the Quadro M2000M wins. If your workload is OpenCL-heavy and server-based, the Tesla M10 wins.

# Specification Differences

The two cards share the same chip, architecture, process node, foundry, transistor count, die size, transistor density, shading units, TMUs, ROPs, memory type, memory bus width, and API support. The differences are in the following fields:

• Base clock: Quadro M2000M at 1,098 MHz versus Tesla M10 at 1,033 MHz (Quadro higher)
• Boost clock: Quadro M2000M at 1,137 MHz versus Tesla M10 at 1,306 MHz (Tesla higher)
• Memory clock: Quadro M2000M at 1,253 MHz (5 Gbps effective) versus Tesla M10 at 1,300 MHz (5.2 Gbps effective) (Tesla higher)
• Memory size: 4 GB versus 8 GB (Tesla double)
• Bandwidth: 80.19 GB/s versus 83.20 GB/s (Tesla higher)
• Pixel rate: 18.19 GPixel/s versus 20.90 GPixel/s (Tesla higher)
• Texture rate: 45.48 GTexel/s versus 52.24 GTexel/s (Tesla higher)
• FP32: 1,455.4 GFLOPS versus 1.672 TFLOPS (Tesla higher)
• TDP: 55 W versus 225 W (Quadro much lower)
• Slot width: MXM Module versus Dual-slot
• Power connectors: None versus 1x 8-pin
• Suggested PSU: None versus 550 W
• Bus interface: MXM-A (3.0) versus PCIe 3.0 x16
• Display outputs: Portable Device Dependent versus No outputs
• Length: Not listed versus 267 mm (10.5 inches)
• Release date: December 2, 2015 versus May 17, 2016

The Quadro M2000M's only clock advantage is the base clock, which is largely irrelevant for performance since boost clocks determine sustained throughput. The Tesla M10 wins every performance-relevant specification except power efficiency and portability.

# FAQ

Q: Which card has a higher average benchmark score?

A: The Quadro M2000M has a slightly higher average score of 9,832 versus the Tesla M10's 9,724, a difference of 1.1%.

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

A: The Tesla M10 wins the Geekbench OpenCL test with a score of 10,318 versus the Quadro M2000M's 10,057, which is a 2.5% advantage.

Q: Which card is better for Vulkan workloads?

A: The Quadro M2000M wins the Geekbench Vulkan test with 9,606 against the Tesla M10's 9,130, a 5.2% lead.

Q: Do both cards have the same memory bus width?

A: Yes, both use a 128-bit bus, but the Tesla M10 has 8 GB of memory compared to the Quadro M2000M's 4 GB.

Q: What are the power requirements for each card?

A: The Quadro M2000M draws 55 W with no external power connectors, while the Tesla M10 draws 225 W and requires a single 8-pin power connector plus a 550 W suggested power supply.

Q: Are these cards still in production?

A: No, both are marked as end-of-life. The Quadro M2000M was released on December 2, 2015, and the Tesla M10 on May 17, 2016.

# The Verdict

The data points to a clear conclusion: choose the Quadro M2000M for mobile, Vulkan-centric professional work, and choose the Tesla M10 for server-based OpenCL compute with larger memory requirements. The Quadro M2000M's 5.2% Vulkan win and 55 W power draw make it the logical pick for laptop workstations where thermal and power constraints are paramount. Its 4 GB memory is sufficient for many mobile professional tasks, and the MXM-A form factor is the only one of these two that fits portable devices.

The Tesla M10 is the compute specialist. Its 2.5% OpenCL win, 8 GB memory capacity, and higher boost clock (1,306 MHz versus 1,137 MHz) make it better suited for headless server deployments where raw throughput and memory capacity matter more than power efficiency. The 225 W power draw and dual-slot design are non-issues in a server chassis, and the 83.20 GB/s bandwidth edges out the Quadro's 80.19 GB/s.

The average scores are close enough that users should not choose between these cards based on overall performance — they are statistically tied at the 47th percentile. The decision comes down to form factor, memory capacity, and API preference. If you are building a mobile workstation and need Vulkan performance, the Quadro M2000M is the only option and it happens to win that test. If you are populating a server rack and need OpenCL compute with 8 GB of memory, the Tesla M10 is the clear answer. Neither card is a bad choice for its intended role; they are simply optimized for different environments. The Quadro M2000M's predecessor is the Quadro Kepler-M and its successor is the Quadro Pascal-M, while the Tesla M10's predecessor is the Tesla Kepler and its successor is the Tesla Pascal, confirming that both cards sit at the same generational point in their respective product lines.