NVIDIA Quadro K4200 vs NVIDIA Tesla K20Xm Comparison

The NVIDIA Tesla K20Xm and NVIDIA Quadro K4200 are both Kepler-generation workstation parts, but they target different corners of the professional market. The data shows a clear performance hierarchy where the Tesla K20Xm holds a decisive advantage in raw compute, while the Quadro K4200 counters with features the Tesla completely lacks. The head-to-head benchmark results quantify this gap: across the single shared test, the Tesla K20Xm wins the only contest, leaving the Quadro K4200 without a single benchmark victory in this comparison.

Head-to-Head Benchmarks

The only directly comparable benchmark in the data is Geekbench OpenCL, and the result is lopsided. The Tesla K20Xm scores 17,215, while the Quadro K4200 manages 12,313. That represents a 39.8% advantage for the Tesla K20Xm, a substantial margin that reflects the fundamental differences in their silicon. This is not a marginal victory; it is a dominant one. The Tesla K20Xm delivers nearly 40% more compute performance in this cross-platform test, which speaks directly to its design as a compute-first accelerator.

Context from the nearestRivals data reinforces the significance of this gap. The Tesla K20Xm’s average benchmark score across all tests is 12,625, while the Quadro K4200’s average is 12,398. Interestingly, the Quadro K4200’s average is only 1.8% below the Tesla K20Xm’s average when all benchmarks are considered, yet the head-to-head OpenCL result shows a 39.8% delta. This suggests the Tesla K20Xm’s OpenCL result is an outlier on the high end, while its other benchmark (Geekbench Metal at 8,035) drags its average down significantly. The Quadro K4200, by contrast, has two results (OpenCL at 12,313 and Vulkan at 12,482) that are much closer together, indicating more consistent performance across different API workloads.

The percentile data shows both cards sit at the 52nd percentile among all GPUs, meaning they occupy a similar overall tier despite the dramatic head-to-head difference. However, the nearestRivals for each card tell a different story. The Tesla K20Xm’s closest rival, the AMD Radeon RX 7600M XT, averages 12,710, which is just 0.7% ahead of the Tesla. The Quadro K4200’s nearest rival, the same AMD card, sits 2.5% ahead. The Tesla K20Xm also edges out the NVIDIA GeForce GTX 670 (12,773, 1.2% behind) and the NVIDIA GeForce GTX 590 (12,830, 1.6% behind). Meanwhile, the Quadro K4200 trails the GeForce GTX 670 by 2.9% and the GeForce GTX 960A by 3.3%. This indicates that while the Tesla K20Xm has a slight edge over its immediate competitors, the Quadro K4200 is positioned slightly lower relative to its own peer group, at least on the Geekbench OpenCL metric.

FAQ

Q: Which GPU is faster in OpenCL compute workloads?

A: The NVIDIA Tesla K20Xm is significantly faster, scoring 17,215 in Geekbench OpenCL compared to the Quadro K4200’s 12,313. This represents a 39.8% performance advantage for the Tesla K20Xm.

Q: Do both cards support the same modern graphics APIs?

A: Yes, both the Tesla K20Xm and the Quadro K4200 report identical API support: DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.2.175. This means software compatibility at the API level is not a differentiator between them.

Q: What is the average benchmark score for each card?

A: The Tesla K20Xm has an average benchmark score of 12,625, while the Quadro K4200 has an average of 12,398. Despite the large head-to-head OpenCL delta, their averages are within 1.8% of each other.

Q: How does the Quadro K4200 compare to its nearest rival, the AMD Radeon RX 7600M XT?

A: The AMD Radeon RX 7600M XT averages 12,710, which is 2.5% ahead of the Quadro K4200’s average score. The Quadro K4200 also trails the NVIDIA GeForce GTX 670 by 2.9%.

Q: Does the Tesla K20Xm have any display outputs?

A: No, the Tesla K20Xm has no display outputs. It is a compute-only accelerator, whereas the Quadro K4200 includes 1x DVI and 2x DisplayPort 1.2 outputs.

Q: What is the transistor density difference between the two chips?

A: The Tesla K20Xm’s GK110 chip has a transistor density of 12.6 million transistors per square millimeter, while the Quadro K4200’s GK104 chip has a density of 12.0 million per square millimeter. Both are built on the same 28 nm process at TSMC.

Architecture Differences

The architectural divide between these two GPUs is stark and explains the benchmark results. The Tesla K20Xm is built on the GK110 chip, a massive design containing 7,080 million transistors on a 561 mm² die. The Quadro K4200 uses the GK104 chip, which is nearly half the size at 3,540 million transistors on a 294 mm² die. Both are fabricated on the same 28 nm process at TSMC, but the GK110 packs nearly twice the hardware — the transistor count difference is exactly 100% more in the Tesla’s favor.

This hardware disparity translates directly into compute resources. The Tesla K20Xm features 2,688 shading units, 224 texture mapping units, and 48 raster output units. The Quadro K4200, by contrast, has 1,344 shading units, 112 TMUs, and 32 ROPs — precisely half the shading units and TMUs, and two-thirds the ROPs. The pixel rate for the Tesla is 40.99 GPixel/s versus 21.95 GPixel/s for the Quadro, and the texture rate is 164.0 GTexel/s versus 87.81 GTexel/s. The FP32 compute throughput tells the same story: 3.935 TFLOPS for the Tesla K20Xm versus 2.107 TFLOPS for the Quadro K4200, an 86.8% advantage for the larger chip.

The memory subsystems also differ fundamentally. The Tesla K20Xm uses a 384-bit memory bus with 6 GB of GDDR5, delivering 249.6 GB/s of bandwidth. The Quadro K4200 has a 256-bit bus with 4 GB of GDDR5, yielding 172.8 GB/s. The Tesla’s bandwidth advantage is roughly 44%. Both use the same memory type, but the Tesla’s wider bus and larger capacity give it a clear edge in data-intensive workloads.

Neither card includes ray tracing cores or tensor cores — these are pure Kepler designs focused on traditional rasterization and compute. The Tesla K20Xm is a dual-slot card with a 235 W TDP, while the Quadro K4200 is a single-slot card with a 108 W TDP. The Tesla also has a longer PCB at 267 mm versus 241 mm for the Quadro. The Tesla’s power connector is not specified in the data, but the Quadro uses a single 6-pin connector.

Specification Differences

The specification sheets reveal a clear segmentation. The Tesla K20Xm uses the GK110 chip, while the Quadro K4200 uses the GK104. Both are 28 nm TSMC parts, but the Tesla’s die is 561 mm² versus 294 mm² for the Quadro, and transistor counts are 7,080 million versus 3,540 million. The Tesla K20Xm has no base or boost clock listed, whereas the Quadro K4200 has a base clock of 771 MHz and a boost clock of 784 MHz. Memory clocks are close: 1300 MHz (5.2 Gbps effective) for the Tesla versus 1350 MHz (5.4 Gbps effective) for the Quadro.

Memory capacity and bus width differ: 6 GB on a 384-bit bus for the Tesla versus 4 GB on a 256-bit bus for the Quadro. Bandwidth is 249.6 GB/s versus 172.8 GB/s. Shading units, TMUs, and ROPs are all higher on the Tesla (2,688/224/48 versus 1,344/112/32). Pixel rate is 40.99 GPixel/s versus 21.95 GPixel/s, and texture rate is 164.0 GTexel/s versus 87.81 GTexel/s. FP32 compute is 3.935 TFLOPS versus 2.107 TFLOPS.

The TDP is a major differentiator: 235 W for the Tesla versus 108 W for the Quadro. The Tesla is dual-slot, the Quadro single-slot. The Tesla has no display outputs, while the Quadro offers 1x DVI and 2x DisplayPort 1.2. The bus interface also differs: the Tesla uses PCIe 3.0 x16, while the Quadro uses PCIe 2.0 x16. The suggested PSU is 550 W for the Tesla versus 300 W for the Quadro. Physical dimensions vary: the Tesla is 267 mm long, while the Quadro is 241 mm long and 111 mm tall. The Tesla’s launch MSRP was 7,699 USD; the Quadro’s launch MSRP is not listed.

The Verdict

The data points to a clear compute hierarchy. The Tesla K20Xm wins the only head-to-head benchmark by a 39.8% margin, and its architectural advantages are overwhelming in raw numbers. It has double the shading units, double the TMUs, 50% more ROPs, 86.8% more FP32 throughput, and 44% more memory bandwidth. For any workload that stresses compute or memory bandwidth, the Tesla K20Xm is the superior choice.

However, the Tesla K20Xm is not a complete product in the traditional sense. It has no display outputs, meaning it cannot drive a monitor. It is a compute accelerator, not a workstation GPU for interactive use. The Quadro K4200, with its DVI and DisplayPort outputs, is a functional workstation card that can render to a screen.

The percentile data complicates the picture. Both cards sit at the 52nd percentile of all GPUs, and their average benchmark scores are within 1.8% of each other. The Tesla K20Xm’s Metal score of 8,035 is notably lower than its OpenCL score, pulling its average down. This suggests the Tesla’s advantage is not universal across all APIs — it excels in OpenCL but may not translate that edge to other frameworks.

For a buyer seeking pure compute density in a server or compute node where display output is irrelevant, the Tesla K20Xm is the data-backed choice. For a professional needing a single-slot card that can both render and compute with lower power draw, the Quadro K4200 is the practical option. The data does not support the Quadro as a compute winner, but it does support it as a more versatile, lower-power alternative.

Where Each One Wins

NVIDIA Tesla K20Xm wins in any scenario that prioritizes raw compute throughput. Its OpenCL score of 17,215 is 39.8% higher than the Quadro’s, and its FP32 rate of 3.935 TFLOPS versus 2.107 TFLOPS gives it a massive edge in number-crunching workloads. The 249.6 GB/s memory bandwidth versus 172.8 GB/s also makes it the winner for memory-bound algorithms. Its larger 6 GB frame buffer versus 4 GB provides more headroom for large datasets. The 235 W TDP and dual-slot design indicate it is built for sustained compute, not power efficiency. The PCIe 3.0 x16 interface also offers double the bandwidth of the Quadro’s PCIe 2.0 x16 in terms of generation, though the data does not provide specific throughput numbers.

NVIDIA Quadro K4200 wins in any scenario requiring display output. It has 1x DVI and 2x DisplayPort 1.2, while the Tesla has none. It also wins on power efficiency, with a 108 W TDP versus 235 W, and its single-slot design fits in more chassis. The suggested PSU requirement of 300 W versus 550 W makes it easier to integrate into existing systems. Its smaller physical footprint (241 mm versus 267 mm length) is an advantage in compact builds. The Quadro’s Vulkan score of 12,482, though not directly comparable to the Tesla’s Metal score, suggests it has respectable performance in modern graphics APIs. The Quadro also has a listed base clock of 771 MHz and boost of 784 MHz, providing defined clock behavior that the Tesla lacks in the specification sheet.

The choice is not about which is objectively better, but which is better for the task. The Tesla K20Xm dominates in compute benchmarks but is useless for visual output. The Quadro K4200 is a jack-of-all-trades with modest compute that can actually show you what it is doing. The data makes this trade-off explicit: one card wins on performance, the other on functionality.