NVIDIA P106-100 vs NVIDIA Tesla K20m Comparison

Head-to-Head Benchmarks

The head-to-head data between the NVIDIA P106-100 and the NVIDIA Tesla K20m is decisively one-sided. Across the two shared benchmark tests, the P106-100 wins both, with the Tesla K20m failing to secure a single victory. The recorded wins tally stands at 2 for the P106-100 and 0 for the Tesla K20m.

The first benchmark, Geekbench OpenCL, shows the most dramatic gap. The P106-100 scores 35,951, while the Tesla K20m manages only 16,241. That is a 121.4% advantage for the P106-100, meaning it more than doubles the Tesla K20m’s raw compute throughput in this OpenCL workload. This is not a marginal lead; it is a generational leap in practical performance. The Tesla K20m, despite having a much larger physical die and more shading units, cannot keep pace with the newer architecture’s efficiency.

The second benchmark, Geekbench Vulkan, narrows the gap somewhat but still favors the P106-100 clearly. The P106-100 scores 32,897, versus the Tesla K20m’s 21,936. The delta here is 50%, a substantial margin that reinforces the P106-100’s overall superiority in modern API workloads. Vulkan is a low-overhead graphics API, and the P106-100’s Pascal architecture handles it far more effectively than the Kepler-based Tesla K20m.

Looking at the broader database context, the P106-100 holds a 68th percentile position among all GPUs, while the Tesla K20m sits at the 64th percentile. The average benchmark score for the P106-100 is 23,249, compared to 19,089 for the Tesla K20m. That difference of roughly 4,160 points translates into a meaningful overall performance tier gap.

Interestingly, the P106-100’s nearest rivals in the database include the AMD Radeon Pro Vega 16 with an average score of 23,250 (a 0% delta), the AMD Radeon RX 6600M at 23,273 (a -0.1% delta), the AMD Radeon R9 M290X at 23,276 (a -0.1% delta), and the AMD Radeon AI PRO R9700 at 23,315 (a -0.3% delta). These rivals are essentially neck-and-neck with the P106-100, which tells you the P106-100 sits right at the top of its performance class. The Tesla K20m, by contrast, is bracketed by the NVIDIA GeForce RTX 4050 Mobile at 19,049 (a 0.2% delta), the AMD Radeon RX 6600 at 19,036 (a 0.3% delta), the NVIDIA Quadro K6000 at 19,030 (a 0.3% delta), and the NVIDIA GeForce GTX 780 at 19,164 (a -0.4% delta). These are all respectable cards, but they are a clear step below the P106-100’s peer group.

The Verdict

From the recorded data alone, the choice is straightforward for most users: the NVIDIA P106-100 is the stronger performer. It wins every shared benchmark, holds a higher percentile rank, and delivers a higher average benchmark score. If your priority is raw speed in OpenCL or Vulkan workloads, the P106-100 is the card the data points to.

However, the Tesla K20m is not without its own rationale. It belongs to the Tesla Kepler generation and carries the legacy of NVIDIA’s compute-focused lineup. Its predecessor is Tesla Fermi and its successor is Tesla Maxwell, placing it in a specific historical context. The database shows it has a 64th percentile rank, which is respectable, and its average score of 19,089 is within striking distance of modern mobile and desktop GPUs like the RTX 4050 Mobile or the RX 6600. For workloads that are not represented in these two benchmark tests, the Tesla K20m’s larger memory bus and different compute characteristics might matter, but the data we have does not support that conclusion.

If you are building a system today and need the best measured performance from these two options, the P106-100 is the clear pick. It offers double the OpenCL performance and 50% more Vulkan performance. The Tesla K20m, while still functional, is effectively outclassed in every metric the database records.

FAQ

Q: Which GPU wins in Geekbench OpenCL?

A: The NVIDIA P106-100 wins with a score of 35,951, compared to the Tesla K20m’s 16,241, a 121.4% advantage.

Q: How does the Tesla K20m compare in Vulkan performance?

A: The Tesla K20m scores 21,936 in Geekbench Vulkan, while the P106-100 scores 32,897. The P106-100 leads by 50%.

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

A: The P106-100 has an average benchmark score of 23,249, while the Tesla K20m has an average of 19,089.

Q: Which card has a higher percentile ranking among all GPUs?

A: The P106-100 ranks in the 68th percentile, while the Tesla K20m ranks in the 64th percentile.

Q: Are there any benchmark tests where the Tesla K20m wins?

A: No. In the head-to-head benchmark data, the Tesla K20m has 0 wins, while the P106-100 has 2 wins.

Q: What is the launch MSRP of the Tesla K20m?

A: The Tesla K20m has a launch MSRP of 3,199 USD.

Specification Differences

The two cards differ in nearly every core specification. The P106-100 uses a GP106 chip, while the Tesla K20m uses a GK110 chip. The P106-100 has 1,280 shading units, 80 texture mapping units, and 48 raster output units. The Tesla K20m has 2,496 shading units, 208 texture mapping units, and 40 raster output units. Despite having nearly double the shading units, the Tesla K20m delivers lower measured performance, which indicates architectural efficiency differences.

Memory configurations also diverge. The P106-100 has 6 GB of GDDR5 memory on a 192-bit bus, yielding a bandwidth of 192.2 GB/s. The Tesla K20m has 5 GB of GDDR5 memory on a 320-bit bus, with a bandwidth of 208.0 GB/s. The Tesla K20m’s wider bus gives it a modest bandwidth advantage, but the P106-100’s higher clocks compensate in practice.

Clock speeds tell part of the story. The P106-100 runs at a base clock of 1506 MHz and a boost clock of 1709 MHz, with memory at 2002 MHz (8 Gbps effective). The Tesla K20m has no listed base or boost clock, and its memory runs at 1300 MHz (5.2 Gbps effective). The P106-100’s memory is significantly faster.

Power and physical requirements differ as well. The P106-100 has a TDP of 120 W, uses a single 6-pin power connector, and a suggested power supply of 300 W. The Tesla K20m has a TDP of 225 W, requires a 6-pin plus an 8-pin connector, and a suggested power supply of 550 W. Both are dual-slot cards with no display outputs. The P106-100 measures 250 mm (9.8 inches) in length, while the Tesla K20m measures 267 mm (10.5 inches).

The bus interface also differs: the P106-100 uses PCIe 1.0 x16, while the Tesla K20m uses PCIe 2.0 x16. In terms of API support, the P106-100 supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. The Tesla K20m supports DirectX 12 (11_0), OpenGL 4.6, and Vulkan 1.2.175.

Architecture Differences

The architectural divide between these two cards is fundamental. The P106-100 is built on the Pascal architecture, fabricated on a 16 nm process at TSMC. It contains 4,400 million transistors on a 200 mm² die, giving it a transistor density of 22.0 million transistors per square millimeter. The Tesla K20m uses the Kepler architecture, fabricated on a 28 nm process, also at TSMC. It contains 7,080 million transistors on a much larger 561 mm² die, resulting in a transistor density of only 12.6 million transistors per square millimeter.

This density difference is key. The Pascal architecture achieves higher performance with fewer transistors and a smaller die, which explains why the P106-100 can outperform the Tesla K20m despite having fewer shading units and less raw transistor count. The P106-100 is also a product of the Mining GPUs generation, whereas the Tesla K20m belongs to the Tesla Kepler (Kxx) generation.

The P106-100 supports FP16 compute at 68.36 GFLOPS (with a 1:64 ratio), while the Tesla K20m has no listed FP16 capability. In FP32, the P106-100 delivers 4.375 TFLOPS, while the Tesla K20m delivers 3.524 TFLOPS. Pixel rate favors the P106-100 at 82.03 GPixel/s versus 36.71 GPixel/s for the Tesla K20m. Texture rate is close: the P106-100 achieves 136.7 GTexel/s, while the Tesla K20m achieves 146.8 GTexel/s. The Tesla K20m’s higher texture rate comes from its 208 TMUs, but this does not translate into a benchmark win.

Neither card has ray tracing cores or tensor cores. Both are end-of-life products. The P106-100 was released on 2017-06-18, while the Tesla K20m was released earlier on 2013-01-04. The Tesla K20m has a documented predecessor (Tesla Fermi) and successor (Tesla Maxwell); the P106-100 has neither listed.

Where Each One Wins

The data points to a clear split in use cases. The NVIDIA P106-100 wins in every measured category: Geekbench OpenCL, Geekbench Vulkan, FP32 throughput, pixel rate, and overall average benchmark score. It is the better choice for any workload that relies on modern APIs like Vulkan or OpenCL compute. Its higher clock speeds, smaller process node, and newer architecture make it more efficient per watt and per transistor. The P106-100 also consumes less power (120 W vs 225 W) and requires a smaller power supply (300 W vs 550 W), making it easier to integrate into existing systems.

The Tesla K20m, on the other hand, has specific advantages that are not reflected in the benchmark suite. It has a wider memory bus (320-bit vs 192-bit), which could benefit memory-bandwidth-intensive tasks that are not captured in the recorded tests. It also has more shading units (2,496 vs 1,280) and more TMUs (208 vs 80), which might matter in workloads that scale with raw shader count rather than architectural efficiency. Its texture rate is slightly higher at 146.8 GTexel/s versus 136.7 GTexel/s. The Tesla K20m’s position in the Tesla product line, with its compute-focused heritage, suggests it was designed for professional and scientific workloads, though the available data does not show it winning any of the recorded benchmarks.

For a practical recommendation: if you are running Vulkan-based games, OpenCL compute tasks, or general GPU acceleration, the P106-100 is the superior choice based on the measurements. If you need the wider memory bus or the specific Tesla ecosystem features, the Tesla K20m has its place, but you will be sacrificing measured performance in the two tests that the database records. The P106-100 wins 2 out of 2 head-to-head benchmarks, and that is the statistic that matters most.