NVIDIA GeForce RTX 2070 SUPER vs NVIDIA Tesla K20m Comparison

The NVIDIA GeForce RTX 2070 SUPER and the NVIDIA Tesla K20m represent two very different eras of GPU design, yet both share an end-of-life status. The data reveals a generational chasm in compute performance, but also a fascinating story about how a workstation-focused accelerator from 2013 holds its own in aggregate metrics. This analysis will break down the benchmark results, architectural shifts, and specific use cases where each card still finds relevance.

Head-to-Head Benchmarks

The head-to-head benchmark data is stark and unequivocal. In the Geekbench OpenCL test, the RTX 2070 SUPER scores 83,358, while the Tesla K20m manages only 16,241. This translates to a delta of 413.3% in favor of the RTX 2070 SUPER — the newer card is over four times faster in this raw compute workload. The results are similarly lopsided in Geekbench Vulkan, where the RTX 2070 SUPER posts 90,637 against the Tesla K20m’s 21,936, a delta of 313.2%. In both available head-to-head tests, the RTX 2070 SUPER wins decisively, capturing all 2 possible wins.

These are not marginal victories; they are generational obliterations. The RTX 2070 SUPER’s lead is so substantial that the Tesla K20m’s scores are closer to a modern integrated GPU than to its rival. Yet, the aggregate picture tells a slightly more nuanced story. The RTX 2070 SUPER’s average benchmark score is 20,282, while the Tesla K20m’s is 19,089 — a difference of roughly 6%. This discrepancy between the head-to-head tests and the average scores suggests that the Tesla K20m excels in other benchmark suites not covered in the direct comparison, likely those that favor its unique architecture or driver optimizations for compute tasks.

Architecture Differences

The architectural gulf between these two cards is the primary driver of their performance disparity. The RTX 2070 SUPER is built on the Turing architecture using the TU104 chip, fabricated on a 12 nm process at TSMC. It packs 13,600 million transistors into a 545 mm² die, yielding a transistor density of 25.0M / mm². In contrast, the Tesla K20m uses the Kepler architecture with the GK110 chip, built on a much older 28 nm process. It contains 7,080 million transistors on a slightly larger 561 mm² die, resulting in a density of just 12.6M / mm². The RTX 2070 SUPER crams nearly twice the transistors into a similar physical space.

The memory subsystems reflect their different eras and purposes. The RTX 2070 SUPER features 8 GB of GDDR6 memory on a 256-bit bus, delivering 448.0 GB/s of bandwidth. The Tesla K20m offers 5 GB of GDDR5 on a wider 320-bit bus, but only achieves 208.0 GB/s bandwidth — less than half the throughput. The RTX 2070 SUPER also brings modern features the Kepler card lacks entirely: 40 RT cores for ray tracing and 320 tensor cores for AI acceleration. The Tesla K20m has neither. The RTX 2070 SUPER supports DirectX 12 Ultimate (12_2) and Vulkan 1.4, while the Tesla K20m is limited to DirectX 12 (11_0) and Vulkan 1.2.175.

The foundation of the RTX 2070 SUPER’s dominance is its raw shader throughput. It offers 2,560 shading units, 160 TMUs, and 64 ROPs, producing 9.062 TFLOPS of FP32 compute. The Tesla K20m has 2,496 shading units, 208 TMUs, and 40 ROPs, yielding only 3.524 TFLOPS FP32 — a 2.5x deficit. The RTX 2070 SUPER also supports FP16 at 18.12 TFLOPS (2:1 ratio), a capability the Tesla K20m lacks entirely. In terms of pixel and texture rates, the RTX 2070 SUPER outputs 113.3 GPixel/s and 283.2 GTexel/s, versus the Tesla K20m’s 36.71 GPixel/s and 146.8 GTexel/s.

Where Each One Wins

Based on the data, the RTX 2070 SUPER is the clear winner in every benchmark category where both cards were tested. Its 413.3% lead in OpenCL and 313.2% lead in Vulkan indicate it is superior for general compute, modern gaming APIs, and any workload that leverages DX12 Ultimate features. The presence of RT and tensor cores means it is future-proof for ray-traced applications and AI inference, areas where the Tesla K20m cannot compete at all.

However, the Tesla K20m’s aggregate performance tells a different story. With an average benchmark score of 19,089, it sits at the 64th percentile of all GPUs, just one point below the RTX 2070 SUPER’s 65th percentile. Its nearest rivals include the NVIDIA Quadro K6000, a fellow Kepler-generation workstation card, and the AMD Radeon RX 6600 (deltaPct 0.3). This suggests the Tesla K20m remains surprisingly competitive in legacy compute benchmarks, likely due to its high TMU count (208) and optimized driver stack for scientific computing. The RTX 2070 SUPER’s rivals include the Intel Arc B570 and A750, indicating it competes in a different performance tier entirely.

The Tesla K20m’s lack of display outputs makes it a compute-only card, while the RTX 2070 SUPER offers 1x HDMI 2.0, 3x DisplayPort 1.4a, and 1x USB Type-C. For workloads that require display output, the RTX 2070 SUPER is the only viable option.

FAQ

Q: Is the RTX 2070 SUPER faster than the Tesla K20m in all benchmarks?

A: Yes, in the two head-to-head tests — Geekbench OpenCL (83,358 vs 16,241) and Geekbench Vulkan (90,637 vs 21,936) — the RTX 2070 SUPER wins both, with deltas of 413.3% and 313.2% respectively.

Q: What is the memory bandwidth difference between the two cards?

A: The RTX 2070 SUPER has 448.0 GB/s of bandwidth from 8 GB of GDDR6 on a 256-bit bus. The Tesla K20m has 208.0 GB/s from 5 GB of GDDR5 on a 320-bit bus.

Q: Does the Tesla K20m support ray tracing or tensor cores?

A: No. The RTX 2070 SUPER has 40 RT cores and 320 tensor cores, while the Tesla K20m lists no RT cores and no tensor cores.

Q: Which card has a higher FP32 compute throughput?

A: The RTX 2070 SUPER delivers 9.062 TFLOPS FP32, while the Tesla K20m delivers 3.524 TFLOPS — a 2.5x advantage for the RTX card.

Q: How do their aggregate benchmark scores compare?

A: The RTX 2070 SUPER has an average benchmark score of 20,282, while the Tesla K20m has 19,089. This is a much smaller gap than the head-to-head tests suggest.

Q: What are the PCIe interface differences?

A: The RTX 2070 SUPER uses PCIe 3.0 x16, while the Tesla K20m uses the older PCIe 2.0 x16 interface.

Specification Differences

| Specification | NVIDIA GeForce RTX 2070 SUPER | NVIDIA Tesla K20m |

|---|---|---|

| Architecture | Turing | Kepler |

| Chip | TU104 | GK110 |

| Process Node | 12 nm | 28 nm |

| Transistors | 13,600 million | 7,080 million |

| Die Size | 545 mm² | 561 mm² |

| Transistor Density | 25.0M / mm² | 12.6M / mm² |

| Memory Size | 8 GB | 5 GB |

| Memory Type | GDDR6 | GDDR5 |

| Memory Bus Width | 256 bit | 320 bit |

| Memory Bandwidth | 448.0 GB/s | 208.0 GB/s |

| Memory Clock | 1750 MHz (14 Gbps effective) | 1300 MHz (5.2 Gbps effective) |

| Shading Units | 2560 | 2496 |

| TMUs | 160 | 208 |

| ROPs | 64 | 40 |

| RT Cores | 40 | None |

| Tensor Cores | 320 | None |

| Pixel Rate | 113.3 GPixel/s | 36.71 GPixel/s |

| Texture Rate | 283.2 GTexel/s | 146.8 GTexel/s |

| FP32 Compute | 9.062 TFLOPS | 3.524 TFLOPS |

| FP16 Compute | 18.12 TFLOPS (2:1) | None |

| TDP | 215 W | 225 W |

| Bus Interface | PCIe 3.0 x16 | PCIe 2.0 x16 |

| Display Outputs | 1x HDMI 2.0, 3x DisplayPort 1.4a, 1x USB Type-C | No outputs |

| DirectX Support | 12 Ultimate (12_2) | 12 (11_0) |

| Vulkan Support | 1.4 | 1.2.175 |

| Release Date | 2019-07-08 | 2013-01-04 |

| Launch MSRP | 499 USD | 3,199 USD |

The Verdict

The data is unambiguous for anyone seeking raw performance: the NVIDIA GeForce RTX 2070 SUPER is the superior card in every measurable metric available. It wins both head-to-head benchmarks with deltas exceeding 300%, offers over 2.5x the FP32 compute, and brings modern features like ray tracing, tensor cores, and DirectX 12 Ultimate support. Its 448.0 GB/s memory bandwidth is more than double the Tesla K20m’s 208.0 GB/s, and it does so while consuming slightly less power (215 W vs 225 W).

The Tesla K20m, however, is not without merit. Its aggregate benchmark score of 19,089 places it in the 64th percentile of all GPUs, remarkably close to the RTX 2070 SUPER’s 20,282 and 65th percentile. This suggests that in specific legacy compute workloads — likely those optimized for Kepler’s high TMU count and CUDA compute capabilities — the K20m remains a viable, if dated, option. Its nearest rivals include the Quadro K6000 and GTX 780, indicating it still trades blows with contemporary mid-range cards from its era.

For a user building a modern system, the RTX 2070 SUPER is the obvious choice. It offers display outputs, supports the latest APIs, and provides a 413.3% advantage in OpenCL compute. For someone maintaining a legacy Tesla-based compute cluster where driver stability and specific Kepler optimizations are paramount, the K20m’s 64th percentile standing shows it can still hold its own in narrow contexts. The data does not support choosing the Tesla K20m for any workload the RTX 2070 SUPER can handle, but it does reveal that the older card’s specialized compute strengths are not entirely obsolete. The RTX 2070 SUPER is the winner for virtually every application, but the Tesla K20m’s aggregate resilience reflects the longevity of NVIDIA’s Kepler architecture in compute-focused environments.