NVIDIA Quadro K5200 vs NVIDIA Tesla K80 Comparison

The NVIDIA Quadro K5200 and NVIDIA Tesla K80 are both end-of-life Kepler-based workstation accelerators from 2014, but they serve fundamentally different purposes. The data shows that in the available Geekbench head-to-head tests, the Quadro K5200 wins both matchups, yet the Tesla K80 counters with superior raw compute specifications and a larger memory pool. This analysis breaks down what those benchmark results mean, where each card excels, and which workload profile each was designed for.

Head-to-Head Benchmarks

The head-to-head comparison consists of two Geekbench tests: OpenCL and Vulkan. In the OpenCL test, the Quadro K5200 scores 19024 against the Tesla K80’s 18620, a 2.2% advantage for the Quadro. In the Vulkan test, the gap widens significantly: the Quadro K5200 posts 20180 versus the Tesla K80’s 19111, giving the Quadro a 5.6% lead. Across both tests, the Quadro wins 2-0, with an average benchmark score of 19602 compared to the Tesla’s 18866.

The Vulkan delta is particularly telling. A 5.6% margin in Vulkan suggests that the Quadro’s higher base clock (667 MHz vs 562 MHz) and boost clock behavior translate more effectively into graphics-oriented workloads. The Tesla K80 does have a higher boost clock (824 MHz vs 771 MHz), but its architecture appears less optimized for the API-level tasks that Vulkan exercises. The Quadro’s 2.2% OpenCL win is narrower, indicating that compute-heavy OpenCL workloads are closer between the two, with the Tesla’s larger shading unit count (2496 vs 2304) partially offsetting its clock disadvantage.

Looking at the nearest rivals for context, the Quadro K5200’s 19602 average sits within 1% of the AMD FirePro D300 (19637, -0.2%) and the AMD Radeon RX 6650 XT (19765, -0.8%), while edging out the AMD Radeon RX 7900 XTX (19410, 1%) and the NVIDIA GeForce GTX 1060 3 GB (19334, 1.4%). The Tesla K80’s 18866 average is similarly competitive, trailing the NVIDIA GeForce RTX 2070 (18789, 0.4%) by a hair, and sitting just below the NVIDIA RTX 2000 Ada Generation (18954, -0.5%), NVIDIA Quadro K6000 (19030, -0.9%), and AMD Radeon RX 6600 (19036, -0.9%). The percentile rankings are close too: the Quadro sits at the 64th percentile of all GPUs, the Tesla at the 63rd.

FAQ

Q: Which card has the higher average benchmark score?

A: The NVIDIA Quadro K5200 leads with an average benchmark score of 19602, while the NVIDIA Tesla K80 averages 18866. That is a 736-point gap, roughly a 3.9% advantage for the Quadro.

Q: Does the Tesla K80 ever win a head-to-head benchmark?

A: No. In the two tests available, the Quadro K5200 wins both: OpenCL (19024 vs 18620, +2.2%) and Vulkan (20180 vs 19111, +5.6%). The Tesla K80 has zero wins in this head-to-head.

Q: How do these cards compare to their nearest rivals?

A: The Quadro K5200’s 19602 average is nearly identical to the AMD FirePro D300 (19637, -0.2%) and AMD Radeon RX 6650 XT (19765, -0.8%), and slightly ahead of the AMD Radeon RX 7900 XTX (19410, 1%). The Tesla K80’s 18866 average is within 0.4% of the NVIDIA GeForce RTX 2070 (18789) and lags the NVIDIA Quadro K6000 (19030) by 0.9%.

Q: What is the memory configuration difference?

A: The Tesla K80 offers 12 GB of GDDR5 on a 384-bit bus with 240.6 GB/s bandwidth. The Quadro K5200 has 8 GB of GDDR5 on a 256-bit bus with 192.3 GB/s bandwidth. The Tesla has 50% more memory capacity and 25% more bandwidth.

Q: Which card has a higher FP32 compute throughput?

A: The Tesla K80 delivers 4.113 TFLOPS FP32, while the Quadro K5200 provides 3.553 TFLOPS. The Tesla’s advantage is approximately 15.8% in raw floating-point throughput.

Q: Are these cards still relevant in modern APIs?

A: Both support DirectX 12 (11_1), OpenGL 4.6, and Vulkan 1.2.175. The Quadro K5200 scores 20180 in Vulkan, which is notably higher than the Tesla K80’s 19111, suggesting the Quadro handles modern graphics APIs more gracefully despite similar API support.

The Verdict

The benchmark data is unambiguous: the Quadro K5200 outperforms the Tesla K80 in both available tests. If the selection criteria are purely based on Geekbench OpenCL and Vulkan scores, the Quadro wins outright with a 2.2% lead in OpenCL and a 5.6% lead in Vulkan. The Quadro’s average score of 19602 also ranks higher in the percentile distribution (64th vs 63rd), reinforcing its edge in general-purpose benchmarking.

However, the Tesla K80’s specification sheet tells a different story for specific workloads. It has more shading units (2496 vs 2304), more texture mapping units (208 vs 192), higher FP32 throughput (4.113 TFLOPS vs 3.553 TFLOPS), and double the memory capacity (12 GB vs 8 GB) with wider bus width (384-bit vs 256-bit) and higher bandwidth (240.6 GB/s vs 192.3 GB/s). These are not trivial differences. The Tesla is built for compute density, not display output — it has no display outputs at all, while the Quadro offers 2x DVI and 2x DisplayPort 1.2.

For users who need a workstation card with display connectivity and better Vulkan performance, the Quadro K5200 is the clear choice. For headless compute servers where FP32 throughput and memory capacity matter more than graphics API performance, the Tesla K80’s raw specs make it a compelling alternative despite losing the benchmarks. The data suggests the Quadro wins the test suite, but the Tesla wins the spec sheet.

Specification Differences

The two cards share several fundamentals: both are 28 nm TSMC parts, both have a die size of 561 mm², both are dual-slot PCIe 3.0 x16 cards, and both are end-of-life. The transistor counts are nearly identical (7,080 million for the Quadro, 7,100 million for the Tesla), and both have 48 ROPs.

The differences are substantial. The Quadro K5200 uses the GK110B chip with a base clock of 667 MHz and boost of 771 MHz, while the Tesla K80 uses the GK210 chip with a lower base of 562 MHz but a higher boost of 824 MHz. Memory differs: the Quadro has 8 GB GDDR5 at 1502 MHz (6 Gbps effective) on a 256-bit bus, yielding 192.3 GB/s; the Tesla has 12 GB GDDR5 at 1253 MHz (5 Gbps effective) on a 384-bit bus, yielding 240.6 GB/s. Shading units are 2304 vs 2496, TMUs are 192 vs 208, and pixel/texture rates are 37.01 GPixel/s and 148.0 GTexel/s for the Quadro versus 42.85 GPixel/s and 171.4 GTexel/s for the Tesla.

Power and physical specs diverge sharply. The Quadro draws 150 W with a 1x 6-pin connector and a suggested 450 W PSU, while the Tesla draws 300 W with a 1x 8-pin connector and a suggested 700 W PSU. Display outputs are the biggest functional split: the Quadro has 2x DVI and 2x DisplayPort 1.2, the Tesla has no outputs. The Quadro measures 267 mm (10.5 inches) long and 111 mm (4.4 inches) high; the Tesla is also 267 mm long but its height is not specified.

Architecture Differences

The Quadro K5200 is built on the Kepler architecture with the GK110B chip, while the Tesla K80 uses Kepler 2.0 with the GK210 chip. This is not a minor revision — the GK210 is designed specifically for compute acceleration, which explains the Tesla’s higher shading unit and TMU counts. The Quadro’s generation is listed as “Quadro Kepler (Kx200)” and its predecessor is Quadro Fermi, with a successor of Quadro Maxwell. The Tesla’s generation is “Tesla Kepler (Kxx)”, with a predecessor of Tesla Fermi and a successor of Tesla Maxwell.

The architectural choices reflect their intended roles. The Quadro’s GK110B is a graphics-first chip, optimized for rendering pipelines and display output. The Tesla’s GK210 doubles down on compute resources: more shading units for parallel throughput, more TMUs for texture-related compute, and a wider memory bus to feed those units. The Tesla’s lower base clock (562 MHz) but higher boost clock (824 MHz) suggests aggressive power management for compute bursts, whereas the Quadro’s steadier clocks (667 MHz base, 771 MHz boost) prioritize consistent graphics performance.

Neither card has ray tracing cores or tensor cores, and neither supports FP16 — both are pure FP32 machines. The transistor density is nearly identical (12.6M / mm² vs 12.7M / mm²), which makes sense given the same process node and die size. The real architectural delta is in how the transistors are allocated: the Quadro invests in display engines and graphics pipelines, while the Tesla invests in raw compute arrays and memory throughput.

Where Each One Wins

The Quadro K5200 wins in every benchmark test available. It takes the OpenCL test by 2.2% and the Vulkan test by 5.6%, and its average score is 3.9% higher. For any workload that relies on Geekbench-style OpenCL or Vulkan execution — which includes general compute kernels and modern graphics API tasks — the Quadro is the faster card. Its display outputs make it the only viable choice for a desktop workstation where a monitor must be connected. The lower 150 W TDP and 450 W suggested PSU also make it far easier to integrate into existing systems.

The Tesla K80 wins where the benchmarks do not measure. Its 12 GB memory capacity is 50% larger than the Quadro’s 8 GB, which matters for datasets that exceed 8 GB. Its 240.6 GB/s bandwidth is 25% higher, which accelerates memory-bound workloads. Its 4.113 TFLOPS FP32 is 15.8% higher, which benefits pure compute kernels. The 300 W TDP and 700 W suggested PSU indicate a card designed for dedicated compute nodes, not desktop towers. The absence of display outputs confirms its headless server role.

In practice, the choice depends on the workload. For an interactive workstation running CAD, visualization, or any task requiring a display, the Quadro K5200 is the only option with outputs, and it also happens to benchmark faster. For a headless server running simulations, data processing, or machine learning inference where FP32 throughput and memory capacity are paramount, the Tesla K80’s specifications outperform the Quadro despite losing the benchmark suite. The data says the Quadro is the better overall GPU; the spec sheet says the Tesla is the better compute accelerator.