NVIDIA Quadro K2200 vs NVIDIA Tesla M10 Comparison

The NVIDIA Quadro K2200 and NVIDIA Tesla M10 are both Maxwell-generation parts built around the same GM107 chip, but they target very different workloads. The benchmark data shows a clear performance hierarchy, with the Quadro K2200 leading in every measured test despite the Tesla M10 carrying twice the memory capacity. This analysis breaks down the raw numbers, contextualizes them against nearest rivals, and outlines which card suits which use case based strictly on the provided facts.

Head-to-Head Benchmarks

The head-to-head comparison consists of two Geekbench tests: OpenCL and Vulkan. In both, the Quadro K2200 emerges as the winner by a healthy margin. In the Geekbench OpenCL test, the Quadro K2200 scores 11,431 points against the Tesla M10’s 10,318 points. That translates to a 10.8% delta in favor of the Quadro. The Vulkan test shows a nearly identical story: the Quadro K2200 scores 10,090 points, while the Tesla M10 manages 9,130 points, a 10.5% advantage for the Quadro.

These are not marginal wins. A 10.8% lead in OpenCL and a 10.5% lead in Vulkan indicate that the Quadro K2200 is consistently faster across both compute APIs. The average benchmark scores reinforce this: the Quadro K2200 sits at 10,761 points, while the Tesla M10 averages 9,724 points. That is a gap of over 1,000 points, or roughly 10.7% on average. The wins tally confirms the sweep: the Quadro K2200 takes both head-to-head tests, leaving the Tesla M10 with zero victories.

Contextualizing the scores against their nearest rivals adds nuance. The Quadro K2200’s average score of 10,761 places it just 0.4% behind the AMD Radeon Pro 450 (10,804) and 1.1% behind the NVIDIA GeForce MX350 (10,883). It edges ahead of the NVIDIA GeForce GTX 560 Ti by 0.7% (10,690) and the AMD Radeon RX 6600S by 1.2% (10,629). The Tesla M10, with its 9,724 average, sits in a different bracket: it is 0.1% ahead of the NVIDIA Tesla C2070 (9,716) and 0.6% ahead of the NVIDIA Quadro P4000 (9,665), but 0.6% behind the NVIDIA GeForce GTX 1070 (9,780) and 0.7% behind the AMD Radeon Pro WX 2100 (9,653). The percentile data tells the same story: the Quadro K2200 ranks in the 49th percentile of all GPUs, while the Tesla M10 sits at the 47th percentile. The Quadro K2200 is the stronger performer in absolute terms, and its rival proximity confirms it is competitive with a slightly higher tier of cards.

The Verdict

The data points to a straightforward conclusion: the NVIDIA Quadro K2200 is the faster GPU in every benchmark recorded here. It wins both head-to-head tests, holds a higher average benchmark score, and ranks higher in the overall percentile distribution. For any workload that relies on OpenCL or Vulkan compute performance, the Quadro K2200 is the superior choice.

The Tesla M10, however, is not without its own rationale. It offers 8 GB of GDDR5 memory, double the Quadro K2200’s 4 GB, and it carries a higher boost clock (1306 MHz vs 1124 MHz). For tasks where memory capacity matters more than raw compute throughput, such as holding larger datasets in VRAM, the Tesla M10 has a structural advantage. But the benchmark results show that this extra memory does not translate into higher scores in the tested workloads.

For a user prioritizing compute performance in OpenCL or Vulkan applications, the Quadro K2200 is the pick. For a user who needs the larger memory footprint and can tolerate lower compute scores, the Tesla M10 is the alternative. The Quadro K2200 also has display outputs (1x DVI, 2x DisplayPort 1.2), while the Tesla M10 has none, making the Quadro the only option for a workstation with a monitor attached. The Tesla M10 is a compute-only accelerator, better suited for server environments where display output is irrelevant.

FAQ

Q: Which GPU has the higher average benchmark score?

A: The NVIDIA Quadro K2200 has an average benchmark score of 10,761, while the NVIDIA Tesla M10 averages 9,724 points.

Q: What is the exact delta between the two in the Geekbench OpenCL test?

A: The Quadro K2200 scores 11,431 points, and the Tesla M10 scores 10,318 points, giving the Quadro a 10.8% lead.

Q: Does the Tesla M10 win any of the head-to-head benchmarks?

A: No. The Tesla M10 loses both the OpenCL and Vulkan tests; the Quadro K2200 wins with deltas of 10.8% and 10.5%, respectively.

Q: How does the Quadro K2200 compare to its nearest rival, the AMD Radeon Pro 450?

A: The Quadro K2200’s average score of 10,761 is 0.4% lower than the Radeon Pro 450’s average of 10,804.

Q: What is the memory capacity difference between the two cards?

A: The Tesla M10 has 8 GB of GDDR5 memory, while the Quadro K2200 has 4 GB of GDDR5 memory.

Q: Which card has a higher boost clock?

A: The Tesla M10 has a boost clock of 1306 MHz, compared to the Quadro K2200’s boost clock of 1124 MHz.

Specification Differences

The two cards share several core specifications but diverge on memory, clocks, power, and physical design. Both use the GM107 chip, have 640 shading units, 40 TMUs, and 16 ROPs. The memory bus is 128-bit for both, and both use GDDR5. The base clocks are close: the Quadro K2200 runs at 1046 MHz, while the Tesla M10 runs at 1033 MHz. The boost clocks differ more significantly, with the Tesla M10 at 1306 MHz versus the Quadro K2200’s 1124 MHz.

Memory capacity is the biggest split: the Tesla M10 has 8 GB, the Quadro K2200 has 4 GB. Memory speed also favors the Tesla M10, which runs at 1300 MHz (5.2 Gbps effective) versus the Quadro K2200’s 1253 MHz (5 Gbps effective). This yields a bandwidth difference of 83.20 GB/s for the Tesla M10 against 80.19 GB/s for the Quadro K2200, a modest 3.8% advantage.

Pixel and texture rates follow the clock speeds. The Tesla M10 achieves 20.90 GPixel/s and 52.24 GTexel/s, while the Quadro K2200 achieves 17.98 GPixel/s and 44.96 GTexel/s. FP32 compute is listed as 1.672 TFLOPS for the Tesla M10 and 1,438.7 GFLOPS for the Quadro K2200, meaning the Tesla M10 has a higher peak theoretical compute. The TDP tells a different story: the Quadro K2200 draws 68 W, while the Tesla M10 draws 225 W. The Quadro is single-slot with no power connectors and a suggested PSU of 250 W; the Tesla M10 is dual-slot, requires a single 8-pin connector, and needs a 550 W PSU. The bus interface also differs: the Quadro K2200 uses PCIe 2.0 x16, while the Tesla M10 uses PCIe 3.0 x16.

Physical dimensions vary as well. The Quadro K2200 is 202 mm (8 inches) long and 111 mm (4.4 inches) high. The Tesla M10 is longer at 267 mm (10.5 inches), with no height listed. Display outputs are another clear separator: the Quadro K2200 has 1x DVI and 2x DisplayPort 1.2, while the Tesla M10 has no outputs at all.

Architecture Differences

Both GPUs are built on the same Maxwell architecture, using the GM107 chip fabricated on a 28 nm process at TSMC. They share identical transistor counts of 1,870 million and a die size of 148 mm², resulting in the same transistor density of 12.6M / mm². Neither card has RT cores or tensor cores, and both support DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.4.

The architectural differences are minimal at the silicon level, but the product positioning differs. The Quadro K2200 belongs to the Quadro Kepler (Kx200) generation, with a predecessor of Quadro Fermi and a successor of Quadro Maxwell. The Tesla M10 belongs to the Tesla Maxwell (Mxx) generation, with a predecessor of Tesla Kepler and a successor of Tesla Pascal. Both are end-of-life products, but the release dates differ: the Quadro K2200 launched in 2014, while the Tesla M10 launched in 2016.

There are no differences in the shading units, TMUs, ROPs, or the underlying chip. The same 640 cores are present in both. The key architectural takeaway is that the Tesla M10 is clocked higher, which boosts its pixel rate, texture rate, and FP32 throughput, but the Quadro K2200 still wins the actual benchmark tests. The higher clocks do not translate into real-world compute victories in the recorded Geekbench results.

Where Each One Wins

The Quadro K2200 wins in every benchmark test recorded here. It is the faster card for OpenCL and Vulkan compute workloads, with leads of 10.8% and 10.5%, respectively. Its higher average benchmark score (10,761 vs 9,724) and better percentile rank (49th vs 47th) reinforce this. The Quadro K2200 is also the only card with display outputs, making it the clear choice for a workstation that needs to drive a monitor while computing. Its lower TDP of 68 W and single-slot design mean it fits into more constrained systems without extra power cabling.

The Tesla M10 wins on memory capacity and bandwidth. Its 8 GB frame buffer is double the Quadro K2200’s 4 GB, and its 83.20 GB/s bandwidth edges out the Quadro’s 80.19 GB/s. It also has a higher boost clock (1306 MHz vs 1124 MHz) and higher peak FP32 throughput (1.672 TFLOPS vs 1,438.7 GFLOPS). These specifications suggest it is better suited for workloads that need to store large datasets in VRAM or that can exploit its higher theoretical compute ceiling, even if the Geekbench results do not reflect that advantage. The Tesla M10’s dual-slot design and 8-pin power connector indicate a server-grade card meant for dedicated compute nodes, not desktop workstations.

In practical terms, the Quadro K2200 is the winner for any user who runs OpenCL or Vulkan applications and needs consistent, validated performance. The Tesla M10 is the pick for a server environment where the lack of display outputs is acceptable and where the extra memory capacity is a hard requirement. The data does not support choosing the Tesla M10 for raw compute speed, but it does offer a clear specification-based reason for memory-heavy tasks.