NVIDIA Quadro K5000 vs NVIDIA Tesla C2070 Comparison

The NVIDIA Tesla C2070 and NVIDIA Quadro K5000 are two end-of-life workstation cards from different NVIDIA generations, and the benchmark data shows a clear split between raw compute throughput and modern API support. The Tesla C2070, built on the Fermi architecture, offers a massive 6 GB frame buffer and a 384-bit memory bus, while the Quadro K5000, from the Kepler generation, counters with a much higher shader count and a smaller, faster memory configuration. The data available shows the Quadro K5000 winning the only direct head-to-head benchmark, but the Tesla C2070 holds its own in the average score comparison, making the choice highly dependent on the specific workload.

Where Each One Wins

The data clearly favors the NVIDIA Quadro K5000 in compute workloads. In the only direct head-to-head benchmark available, Geekbench OpenCL, the Quadro K5000 scores 11,418 points against the Tesla C2070's 9,716 points. This represents a 14.9% advantage for the K5000, a significant margin that indicates a substantial lead in general-purpose GPU compute tasks. The K5000’s architecture, with 1,536 shading units and a peak FP32 throughput of 2.169 TFLOPS, is the primary driver of this performance, vastly outpacing the Tesla C2070’s 448 shading units and 1,027.7 GFLOPS FP32 rate.

The NVIDIA Tesla C2070 wins in the field of memory capacity and bandwidth density. Its 6 GB of GDDR5 memory on a 384-bit bus provides a large pool for datasets that exceed the K5000's 4 GB capacity. While the K5000 has a higher total bandwidth (172.8 GB/s vs. 143.4 GB/s), the C2070’s larger frame buffer is a distinct advantage for applications that need to hold entire models or large textures in VRAM without spilling over to system memory. The C2070 also has a higher transistor density of 12.0M/mm², but that is not a performance metric.

Beyond raw compute and memory, the K5000 wins on feature support. It is the only card of the two to offer Vulkan support (version 1.2.175), and its benchmark results include a Geekbench Vulkan score of 11,169 and a Geekbench Metal score of 6,324, indicating it is capable of running modern graphics APIs. The Tesla C2070, in contrast, has no Vulkan or Metal benchmark scores listed, and its DirectX support is listed as 12 (11_0), the same as the K5000, but its feature set is more dated.

The Verdict

The data points to a decisive victory for the NVIDIA Quadro K5000 for most users. It is the faster card in the OpenCL compute test, has a significantly higher peak FP32 performance (2.169 TFLOPS vs. 1,027.7 GFLOPS), and offers broader API support, including Vulkan. The K5000 also achieves this with a lower power draw, with a TDP of 122 W compared to the C2070's 238 W, and a lower suggested PSU of 300 W versus 550 W.

The NVIDIA Tesla C2070 is the pick only for a very specific scenario: when the 6 GB memory capacity is non-negotiable. If a workload requires more than the 4 GB offered by the K5000, the C2070 becomes the only viable option from this pair, despite its lower compute performance. However, for any task that fits within the K5000's memory footprint, the Quadro is the superior choice based on the benchmark results.

The average benchmark scores reinforce this hierarchy. The Tesla C2070 has an average benchmark score of 9,716, placing it in the 47th percentile of all GPUs. The Quadro K5000, with an average score of 9,637, sits in the 46th percentile. While the C2070 has a slightly higher average score, this is an artifact of the K5000's average being lowered by its additional Metal and Vulkan benchmark results, which are not present for the C2070. In the direct comparison, the K5000 is clearly faster.

Head-to-Head Benchmarks

The sole head-to-head benchmark, Geekbench OpenCL, tells a clear story. The Quadro K5000 achieves a score of 11,418, while the Tesla C2070 scores 9,716. This yields a delta of -14.9% for the C2070, meaning the K5000 is 14.9% faster. This is the decisive metric for compute performance and aligns with the theoretical specifications, where the K5000's FP32 throughput is more than double that of the C2070.

The K5000's victory is not just a single point. The benchmark result shows a K5000 Vulkan score of 11,169, which is close to its OpenCL score of 11,418. This suggests that the Kepler architecture scales well across different compute APIs, making it a more versatile performer. The Tesla C2070 has no comparable data for other APIs, which limits its appeal in modern applications that can leverage Vulkan.

FAQ

Q: Which card has the higher average benchmark score?

A: The NVIDIA Tesla C2070 has a slightly higher average benchmark score of 9,716, compared to the Quadro K5000's 9,637. However, the K5000 wins the direct OpenCL benchmark.

Q: Is the Quadro K5000 faster in compute workloads?

A: Yes. In the Geekbench OpenCL test, the Quadro K5000 scores 11,418, which is 14.9% higher than the Tesla C2070's score of 9,716.

Q: Which card has more memory?

A: The NVIDIA Tesla C2070 has 6 GB of GDDR5 memory, while the NVIDIA Quadro K5000 has 4 GB of GDDR5 memory.

Q: Does the Tesla C2070 support the Vulkan API?

A: No. The data lists no Vulkan support for the Tesla C2070. The Quadro K5000 supports Vulkan version 1.2.175.

Q: What is the difference in peak FP32 performance?

A: The Quadro K5000 has a peak FP32 performance of 2.169 TFLOPS, which is more than double the Tesla C2070's 1,027.7 GFLOPS.

Q: Which card has a lower power consumption?

A: The NVIDIA Quadro K5000 has a TDP of 122 W, which is significantly lower than the Tesla C2070's 238 W TDP.

Architecture Differences

The two cards represent distinct architectural generations from NVIDIA. The Tesla C2070 is based on the Fermi architecture, using the GF100 chip, while the Quadro K5000 is built on the Kepler architecture with the GK104 chip. This generational leap is the root cause of their performance differences.

The manufacturing process differs significantly. The Tesla C2070 uses a 40 nm process node, resulting in a large die size of 529 mm² housing 3,100 million transistors. In contrast, the Quadro K5000 is fabricated on a 28 nm process, allowing for a smaller 294 mm² die that contains 3,540 million transistors. This leads to a transistor density of 12.0M/mm² for the K5000, more than double the 5.9M/mm² of the C2070, enabling the Kepler chip to pack more compute resources into a smaller area.

The core configurations are starkly different. The Quadro K5000 has 1,536 shading units, 128 texture mapping units (TMUs), and 32 raster output units (ROPs). The Tesla C2070, with its older Fermi design, has only 448 shading units, 56 TMUs, and 48 ROPs. This difference in shader count is the primary reason for the K5000's superior compute performance. The K5000 also has a higher pixel rate (22.59 GPixel/s) and texture rate (90.37 GTexel/s) compared to the C2070's 16.07 GPixel/s and 32.14 GTexel/s.

Memory architecture also diverges. The C2070 uses a 384-bit memory bus with 6 GB of GDDR5, while the K5000 uses a 256-bit bus with 4 GB. This means the C2070 has a larger capacity but a lower bandwidth (143.4 GB/s) than the K5000 (172.8 GB/s). The K5000 also has a higher clocked memory, with 5.4 Gbps effective speed compared to the C2070's 3 Gbps effective speed.

Other differences include physical and power characteristics. The K5000 is a longer card at 267 mm (10.5 inches) with a height of 111 mm (4.4 inches), while the C2070 is 248 mm (9.8 inches) long with no listed height. The K5000 uses a single 6-pin power connector and has a suggested PSU of 300 W, while the C2070 requires a 6-pin and an 8-pin connector and suggests a 550 W PSU. The K5000 offers more display outputs (2x DVI and 2x DisplayPort 1.2) compared to the C2070's single DVI output. The Quadro K5000 also has a launch MSRP of 2,499 USD, while the Tesla C2070 has no listed launch MSRP.