NVIDIA Quadro K2200 vs NVIDIA Tesla C2075 Comparison

The NVIDIA Quadro K2200 and NVIDIA Tesla C2075 are both end-of-life professional GPUs, but the benchmark data shows they serve very different performance tiers. In the only head-to-head benchmark available, the Quadro K2200 decisively outperforms the Tesla C2075, posting a 9.9% higher score in Geekbench OpenCL. This result, combined with architectural differences, makes the Quadro K2200 the clear choice for general compute and workstation tasks, while the Tesla C2075 retains a niche for specific legacy memory-heavy workloads.

Head-to-Head Benchmarks

The sole direct comparison between these two cards is the Geekbench OpenCL test, and the results are unambiguous. The Quadro K2200 scores 11,431 points, while the Tesla C2075 manages 10,400 points. This translates to a 9.9% advantage for the Quadro K2200, a significant margin that establishes it as the faster compute card in this pairing.

Delving into the broader benchmark context, the Quadro K2200’s average benchmark score is 10,761, placing it at the 49th percentile of all GPUs. Its nearest rivals include the AMD Radeon Pro 450 (10,804 score, -0.4% delta) and the AMD Radeon RX 6600S (10,629 score, 1.2% delta), showing it sits in a competitive mid-range compute band. The Tesla C2075, by contrast, has an average benchmark score of 10,400, placing it at the 48th percentile. Its nearest rivals, such as the AMD Radeon RX 6500M (10,362 score, 0.4% delta) and the AMD Radeon R9 M275X (10,582 score, -1.7% delta), indicate it is clustered in a similar performance neighborhood, yet the Quadro K2200 still emerges ahead.

The win count is 1-0 in favor of the Quadro K2200. While a single benchmark is not exhaustive, the data consistently points to the Quadro K2200 having a higher compute ceiling. The Quadro K2200 also demonstrates versatility with a Geekbench Vulkan score of 10,090, a test the Tesla C2075 does not have a recorded score for. This suggests the Quadro K2200 is not only faster in raw OpenCL compute but also offers a broader feature set for modern API workloads.

The Verdict

For any user prioritizing raw compute performance, the NVIDIA Quadro K2200 is the definitive winner. Its 9.9% lead in OpenCL performance is substantial and directly translates to faster rendering, simulation, and data processing in applications that leverage this API. The Quadro K2200’s higher average benchmark score of 10,761 versus 10,400 for the Tesla C2075 reinforces this conclusion.

The Quadro K2200 is the better all-round card for modern workstations. It offers a Vulkan score of 10,090, indicating support for a contemporary graphics API that the Tesla C2075 lacks entirely. Furthermore, the Quadro K2200 is a more efficient and practical piece of hardware, with a 68 W TDP compared to the Tesla C2075’s 247 W, and it requires only a 250 W suggested PSU versus a 550 W unit for the Tesla. The Tesla C2075’s dual-slot design and requirement for multiple power connectors also make it a more demanding installation.

The Tesla C2075 is not without its merits, but they are specific. Its 6 GB of memory, compared to the Quadro K2200’s 4 GB, and its significantly wider 384-bit memory bus, which delivers 150.3 GB/s of bandwidth versus 80.19 GB/s, make it a potential choice for workloads where memory capacity and bandwidth are the absolute bottleneck. However, this advantage is not reflected in the compute benchmark, where it loses. For the vast majority of tasks, the Quadro K2200 is the superior choice. The Tesla C2075 should only be considered by users with a specific, legacy application that is proven to benefit from its large memory pool and is not sensitive to its lower compute throughput.

Architecture Differences

The two cards are built on fundamentally different architectures, explaining their performance characteristics. The Quadro K2200 is based on the GM107 chip using the Maxwell architecture, fabricated on a 28 nm process at TSMC. It packs 1,870 million transistors onto a 148 mm² die, resulting in a transistor density of 12.6M per mm². In contrast, the Tesla C2075 uses the GF110 chip with the older Fermi 2.0 architecture, also from TSMC but on a larger 40 nm process. This chip contains 3,000 million transistors on a massive 520 mm² die, but its density is lower at 5.8M per mm².

These architectural differences lead to divergent compute configurations. The Quadro K2200 has 640 shading units, 40 texture mapping units (TMUs), and 16 raster operation units (ROPs). The Tesla C2075 has fewer shading units at 448, but more TMUs (56) and ROPs (48). The Maxwell architecture’s efficiency is evident: despite fewer transistors per square millimeter, the Quadro K2200 achieves a higher FP32 performance of 1,438.7 GFLOPS compared to the Tesla C2075’s 1,027.7 GFLOPS. This is a clear victory for the newer, more efficient Maxwell design.

Memory architecture is another major divergence. The Quadro K2200 uses 4 GB of GDDR5 on a 128-bit bus, yielding 80.19 GB/s of bandwidth. The Tesla C2075 uses 6 GB of GDDR5 on a 384-bit bus, delivering nearly double the bandwidth at 150.3 GB/s. The Tesla’s memory clock is 783 MHz (3.1 Gbps effective), while the Quadro’s is 1253 MHz (5 Gbps effective), showing the Quadro compensates for its narrower bus with faster memory. The Tesla C2075 also lacks support for Vulkan, while the Quadro K2200 supports version 1.4. Both support DirectX 12 (11_0) and OpenGL 4.6.

FAQ

Q: Which GPU is faster in compute performance?

A: The NVIDIA Quadro K2200. It wins the head-to-head Geekbench OpenCL benchmark with a score of 11,431 versus 10,400 for the Tesla C2075, a 9.9% difference. Its FP32 performance is also higher at 1,438.7 GFLOPS compared to 1,027.7 GFLOPS.

Q: Does the Tesla C2075 have any performance advantage?

A: Yes, in memory bandwidth. The Tesla C2075 has a 384-bit memory bus and 150.3 GB/s bandwidth, while the Quadro K2200 has a 128-bit bus and 80.19 GB/s. It also has more memory (6 GB vs 4 GB).

Q: Which card is more power-efficient?

A: The Quadro K2200 is dramatically more efficient. It has a 68 W TDP and requires a 250 W suggested PSU, while the Tesla C2075 has a 247 W TDP and requires a 550 W suggested PSU.

Q: Which card supports the Vulkan API?

A: Only the Quadro K2200 supports Vulkan, with version 1.4. The Tesla C2075 has no Vulkan support listed.

Q: What are the physical differences between the two cards?

A: The Quadro K2200 is a single-slot card measuring 202 mm in length (8 inches), while the Tesla C2075 is a dual-slot card measuring 248 mm (9.8 inches). The Tesla also requires a 6-pin and an 8-pin power connector, while the Quadro requires none.

Q: Which card has a higher average benchmark score?

A: The Quadro K2200 has an average benchmark score of 10,761, placing it at the 49th percentile. The Tesla C2075 has an average score of 10,400, placing it at the 48th percentile.

Where Each One Wins

The NVIDIA Quadro K2200 wins in all compute-centric categories based on the data. It is the faster card in the OpenCL benchmark, the only direct comparison available. Its higher FP32 performance (1,438.7 GFLOPS) and higher pixel rate (17.98 GPixel/s vs 16.07 GPixel/s) and texture rate (44.96 GTexel/s vs 32.14 GTexel/s) indicate superior throughput for graphics and general-purpose compute tasks. It also wins on efficiency, with a lower TDP and smaller physical footprint, and is the only one of the two to support the modern Vulkan API. This makes it the clear winner for any modern workstation application, from 3D modeling to video editing and scientific computing that leverages OpenCL or Vulkan.

The NVIDIA Tesla C2075 wins specifically in memory capacity and bandwidth. Its 6 GB frame buffer is 50% larger than the Quadro K2200’s 4 GB. More importantly, its 384-bit memory bus provides 150.3 GB/s of bandwidth, which is 87% higher than the Quadro’s 80.19 GB/s. This makes the Tesla C2075 a potential choice for a narrow set of workloads that are exceptionally memory-intensive, such as processing very large datasets that cannot fit in a 4 GB frame buffer and where the lower compute performance is not the limiting factor. However, this is a niche advantage, as the compute benchmark does not reflect a real-world benefit for this configuration.

Specification Differences

The two cards differ in nearly every core specification. The process node is a key differentiator: the Quadro K2200 uses a 28 nm process, while the Tesla C2075 uses a larger 40 nm process. This leads to a difference in transistor count and die size, with the Quadro having 1,870 million transistors on a 148 mm² die, and the Tesla having 3,000 million on a 520 mm² die. Clock speeds also differ, with the Quadro K2200 having a base clock of 1046 MHz and a boost clock of 1124 MHz, while the Tesla C2075 has no listed base or boost clocks, only a memory clock of 783 MHz (3.1 Gbps effective). The Quadro’s memory clock is 1253 MHz (5 Gbps effective).

The memory subsystems are completely different. The Quadro K2200 has 4 GB of GDDR5 on a 128-bit bus, while the Tesla C2075 has 6 GB of GDDR5 on a 384-bit bus. The compute cores also differ: the Quadro has 640 shading units, 40 TMUs, and 16 ROPs, while the Tesla has 448 shading units, 56 TMUs, and 48 ROPs. Power requirements are starkly different, with the Quadro at 68 W TDP and the Tesla at 247 W TDP, and the physical cards differ in slot width (single vs dual) and power connectors (none vs 1x 6-pin + 1x 8-pin). The Quadro K2200 also offers multiple display outputs (1x DVI and 2x DisplayPort 1.2), while the Tesla C2075 only has a single DVI output. The Tesla C2075 does not support Vulkan, while the Quadro K2200 supports Vulkan 1.4.