NVIDIA Quadro K4200 vs NVIDIA Tesla K10 Comparison

Head-to-Head Benchmarks

The recorded data contains only one direct head-to-head benchmark between the NVIDIA Tesla K10 and the NVIDIA Quadro K4200: the Geekbench OpenCL test. In that test, the Tesla K10 scores 14,029 points, while the Quadro K4200 scores 12,313 points. The Tesla K10 comes out ahead by 13.9%, a substantial margin that reflects its higher compute throughput.

Looking closer at the raw specifications, this OpenCL result makes sense. The Tesla K10 carries 1,536 shading units against the Quadro K4200's 1,344, a difference of 192 units. Its texture units also outnumber the Quadro's, 128 versus 112. The Tesla K10 achieves 2.289 TFLOPS of FP32 compute, while the Quadro K4200 reaches 2.107 TFLOPS. That is roughly an 8.6% theoretical peak advantage for the Tesla K10, yet the measured benchmark gap is larger at 13.9%. The discrepancy suggests that memory bandwidth also plays a role. Although both cards use 4 GB of GDDR5 on a 256-bit bus, the Tesla K10's memory runs at 1250 MHz (5 Gbps effective), yielding 160.0 GB/s of bandwidth, while the Quadro K4200's memory runs at 1350 MHz (5.4 Gbps effective), yielding 172.8 GB/s. Here the Quadro K4200 actually has the bandwidth advantage, about 8% higher, so the Tesla K10's win cannot be attributed to raw memory speed.

What explains the larger-than-expected gap? The Tesla K10's higher pixel rate, 23.84 GPixel/s versus 21.95 GPixel/s, and higher texture rate, 95.36 GTexel/s versus 87.81 GTexel/s, both point to a more fully enabled GK104 implementation. The K10's shading core count is 14.3% higher than the K4200's, which closely matches the 13.9% benchmark delta. In other words, the OpenCL result aligns almost perfectly with the shader count difference, while the memory bandwidth difference only partially offsets that compute advantage. The data indicates the Tesla K10 wins the only recorded head-to-head test, and it does so by a margin consistent with its hardware configuration.

It is notably the Geekbench Vulkan test is only recorded for the Quadro K4200, with a score of 12,482, and there is no corresponding Vulkan score for the Tesla K10 in the database. Without a matched Vulkan result, no direct comparison can be made on that API. Similarly, the Tesla K10 has only one benchmark entry, while the Quadro K4200 has two, but the only overlapping test is OpenCL.

FAQ

Q: Which GPU wins the Geekbench OpenCL benchmark?

A: The NVIDIA Tesla K10 wins with a score of 14,029 against the NVIDIA Quadro K4200's 12,313, a delta of 13.9%.

Q: How does the Tesla K10 compare to its nearest rivals?

A: The Tesla K10's average benchmark score is 14,029. It sits 0.9% behind the NVIDIA GeForce GTX 680 (14,150), and it is 1.1% ahead of the AMD Radeon RX 570X (13,871), 1.5% ahead of the NVIDIA RTX A2000 Mobile (13,821), and 1.6% ahead of the AMD Radeon 660M (13,812).

Q: How does the Quadro K4200 compare to its nearest rivals?

A: The Quadro K4200's average benchmark score is 12,398. It is 1.8% behind the NVIDIA Tesla K20Xm (12,625), 2.5% behind the AMD Radeon RX 7600M XT (12,710), 2.9% behind the NVIDIA GeForce GTX 670 (12,773), and 3.3% ahead of the NVIDIA GeForce GTX 960A (11,998).

Q: Do both cards have the same memory size and bus width?

A: Yes, both have 4 GB of GDDR5 memory on a 256-bit bus. However, the Quadro K4200's memory speed is faster at 1350 MHz (5.4 Gbps effective), giving it 172.8 GB/s of bandwidth, while the Tesla K10 runs at 1250 MHz (5 Gbps effective) for 160.0 GB/s.

Q: Do both cards support the same API versions?

A: Yes, both report DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.2.175. Neither has recorded FP16 capability listed, and neither has ray tracing or tensor cores.

Q: What is the percentile ranking for each GPU in the database?

A: The Tesla K10 ranks in the 55th percentile among all GPUs, while the Quadro K4200 ranks in the 52nd percentile.

Architecture Differences

Both the NVIDIA Tesla K10 and the NVIDIA Quadro K4200 are built on the Kepler architecture, using the same GK104 chip manufactured by TSMC on a 28 nm process. Both have the same transistor count of 3,540 million and the same die size of 294 mm², giving both a transistor density of 12.0M / mm². The architecture generation labels differ slightly: the Tesla K10 is listed under "Tesla Kepler (Kxx)", while the Quadro K4200 is under "Quadro Kepler (Kx200)", but these are product family designations rather than architectural changes.

The key architectural difference lies in how each GPU is configured within the GK104 die. The Tesla K10 implements 1,536 shading units, 128 texture mapping units, and 32 ROPs. The Quadro K4200 implements 1,344 shading units, 112 texture mapping units, and 32 ROPs. Both have the same ROP count, so pixel fill operations are less differentiated, but the Tesla K10 has 14.3% more shaders and 14.3% more TMUs. This is a classic binning pattern: the same chip, with the Tesla K10 having more active execution resources.

Neither GPU has ray tracing cores or tensor cores, and neither lists FP16 performance. Both support DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.2.175. The Tesla K10's production status is end-of-life, as is the Quadro K4200's. The Tesla K10's predecessor is Tesla Fermi and its successor is Tesla Maxwell; the Quadro K4200's predecessor is Quadro Fermi and its successor is Quadro Maxwell. These lineage labels reflect the generational progression within each product family, not differences in the underlying silicon generation.

The memory architecture is identical in capacity, type, and bus width: 4 GB GDDR5 on a 256-bit interface. The bandwidth differs due to clock speeds, with the Quadro K4200 at 172.8 GB/s versus the Tesla K10 at 160.0 GB/s. The Quadro K4200 also has a higher memory clock in MHz terms: 1350 MHz versus 1250 MHz. This makes the Quadro K4200 the better memory-subsystem performer on paper, even though it falls behind in compute resources.

Specification Differences

The most consequential specification difference is the shading unit count: 1,536 on the Tesla K10 versus 1,344 on the Quadro K4200. This drives the compute performance gap. The TMU count also differs: 128 versus 112. The ROP count is the same at 32 on both. Pixel rate and texture rate follow the execution resource counts: the Tesla K10 achieves 23.84 GPixel/s and 95.36 GTexel/s, while the Quadro K4200 achieves 21.95 GPixel/s and 87.81 GTexel/s. FP32 compute is 2.289 TFLOPS on the Tesla K10 versus 2.107 TFLOPS on the Quadro K4200.

Power and physical design differ substantially. The Tesla K10 has a TDP of 225 W and requires a dual-slot cooler, a 1x 6-pin plus 1x 8-pin power connector setup, and a suggested PSU of 550 W. The Quadro K4200 has a TDP of 108 W, fits in a single slot, uses a single 1x 6-pin power connector, and lists a suggested PSU of 300 W. The Tesla K10 is also longer at 272 mm (10.7 inches), while the Quadro K4200 is 241 mm (9.5 inches) long and has a recorded height of 111 mm (4.4 inches). The Tesla K10 has no recorded height or width.

The bus interface differs: the Tesla K10 uses PCIe 3.0 x16, while the Quadro K4200 uses PCIe 2.0 x16. This could affect data transfer rates in some workloads, though the compute benchmark data does not isolate this effect. Display outputs also differ: the Tesla K10 has no outputs, while the Quadro K4200 has 1x DVI and 2x DisplayPort 1.2. This is a fundamental product positioning difference. The Tesla K10 is a compute-oriented card with no display capability, while the Quadro K4200 is a workstation card with display outputs.

Clock behavior differs as well. The Quadro K4200 has recorded base and boost clocks of 771 MHz and 784 MHz, respectively. The Tesla K10 has no recorded base or boost clock in the database. The memory clock differs: 1250 MHz (5 Gbps effective) on the Tesla K10 versus 1350 MHz (5.4 Gbps effective) on the Quadro K4200. The Tesla K10 has a launch MSRP of 5,099 USD, while the Quadro K4200 has no launch MSRP listed. Release dates differ: the Tesla K10 was released on 2012-04-30, and the Quadro K4200 on 2014-07-21.

Where Each One Wins

The Tesla K10 wins the only overlapping benchmark, the Geekbench OpenCL test, by 13.9%. It also has the higher peak FP32 compute, the higher pixel rate, the higher texture rate, and more shading units and TMUs. For any workload that is purely compute-bound and does not depend on memory bandwidth, the Tesla K10 should be faster. The data also shows the Tesla K10 has no display outputs, so it is suited for headless compute tasks such as render farms, simulation, or general-purpose GPU compute where display output is unnecessary.

The Quadro K4200 wins in several non-compute categories. It has higher memory bandwidth at 172.8 GB/s versus 160.0 GB/s. It has a much lower TDP at 108 W versus 225 W, making it far easier to cool and power. It is a single-slot card, while the Tesla K10 is dual-slot. It uses only a 1x 6-pin power connector and suggests a 300 W PSU, versus the Tesla K10's 1x 6-pin plus 1x 8-pin and 550 W suggestion. The Quadro K4200 also has display outputs (1x DVI, 2x DisplayPort 1.2), so it can drive monitors. Its PCIe 2.0 x16 interface is older than the Tesla K10's PCIe 3.0 x16, but that does not affect its display capability. The Quadro K4200 also has a recorded Vulkan benchmark score of 12,482, which indicates it can run Vulkan workloads, though there is no Tesla K10 Vulkan score for comparison.

The thermal and physical advantages of the Quadro K4200 are significant for workstation deployment. A single-slot card that draws 108 W and requires only a 6-pin connector can fit into denser chassis configurations. The Tesla K10's 225 W TDP and dual-slot cooler require more airflow and more power headroom. The Quadro K4200's shorter length, 241 mm versus 272 mm, also improves case compatibility.

The Verdict

The database shows a clear performance hierarchy: the Tesla K10 is the faster compute card, winning the sole head-to-head OpenCL benchmark by 13.9% and ranking in the 55th percentile of all GPUs, versus the Quadro K4200's 52nd percentile. Anyone choosing between these two based purely on computational throughput should select the Tesla K10. Its higher shader count, TMU count, pixel rate, texture rate, and FP32 TFLOPS all point in the same direction.

However, the Quadro K4200 is the more practical workstation card. It has display outputs, a far lower TDP of 108 W versus 225 W, a single-slot form factor, a single 6-pin power connector, a suggested PSU of 300 W versus 550 W, and a shorter physical length. It also has higher memory bandwidth, 172.8 GB/s versus 160.0 GB/s, which could benefit memory-bound workloads despite its lower compute peak. The Quadro K4200's PCIe 2.0 x16 interface is a limitation relative to the Tesla K10's PCIe 3.0 x16, but that matters less for display-oriented tasks.

The release dates also matter for context. The Tesla K10 launched on 2012-04-30, while the Quadro K4200 launched on 2014-07-21. Both are end-of-life. The Tesla K10 carries a launch MSRP of 5,099 USD, while the Quadro K4200 has no listed launch MSRP. The Tesla K10 belongs to the Tesla Kepler generation with a Tesla Fermi predecessor and Tesla Maxwell successor lineage, while the Quadro K4200 belongs to the Quadro Kepler generation with Quadro Fermi predecessor and Quadro Maxwell successor lineage.

The verdict: pick the Tesla K10 for headless compute tasks where raw OpenCL performance is the only metric that matters. Pick the Quadro K4200 for a workstation role that needs display output, lower power draw, and a smaller physical footprint, accepting the 13.9% slower OpenCL score in exchange for better memory bandwidth and a single-slot cooler. The data does not support recommending the Quadro K4200 as the faster card, but it does support describing it as the more efficient one with lower system demands.