GPU Comparison

The NVIDIA GeForce RTX 2070 and the NVIDIA Tesla K40c represent two very different eras of GPU design, separated by five years of architectural evolution. The data shows a clear overall winner in the RTX 2070, which delivers a Geekbench OpenCL score of 79,966 compared to the K40c’s 17,468, a staggering 357.8% advantage. However, the Tesla K40c is not without its own distinct characteristics, particularly its larger 12 GB memory pool and higher shading unit count. The RTX 2070 is the definitive choice for modern, API-heavy workloads and general compute, while the K40c’s relevance is confined to legacy compute tasks that can leverage its unique memory configuration. This analysis will dissect the architectural, benchmark, and specification differences to determine which GPU suits which specific use case, strictly based on the provided data.

The Verdict

Based solely on the benchmark data, the NVIDIA GeForce RTX 2070 is the superior performer. It wins the only head-to-head benchmark available, Geekbench OpenCL, by a margin of 357.8%. This single data point is decisive, indicating that the RTX 2070 offers a dramatically higher level of compute performance for OpenCL workloads. Its average benchmark score of 18,789 also places it above the K40c’s average of 17,468, reinforcing its overall performance lead.

The Tesla K40c, conversely, finds its niche not in raw speed but in its memory capacity. With 12 GB of VRAM, it offers 50% more memory than the RTX 2070’s 8 GB. For specific workloads that are memory-bound and require large datasets to reside on the GPU, this capacity advantage could be a deciding factor, even if the processing speed is significantly lower. The RTX 2070 is the pick for users prioritizing compute throughput, modern API support, and efficiency. The K40c is a specialist tool for legacy compute tasks where its 12 GB frame buffer is a non-negotiable requirement, and its lower performance is an acceptable trade-off. The data does not support picking the K40c for any general-purpose or gaming scenario.

Architecture Differences

The architectural chasm between these two GPUs is vast. The RTX 2070 is built on the Turing architecture, utilizing a 12 nm process at TSMC, while the K40c is based on the older Kepler architecture, fabricated on a 28 nm process. This process difference is a primary driver of the performance gap, allowing the RTX 2070 to pack 10,800 million transistors into a smaller 445 mm² die, resulting in a transistor density of 24.3M / mm². The K40c, in contrast, has fewer transistors (7,080 million) spread over a larger 561 mm² die, giving it a much lower density of 12.6M / mm².

The most significant feature differences are the inclusion of dedicated hardware in the RTX 2070. It has 36 RT cores and 288 tensor cores, which are entirely absent from the K40c. This means the RTX 2070 is capable of hardware-accelerated ray tracing and AI-driven tasks like DLSS, while the K40c has no such capabilities. Furthermore, the RTX 2070 supports a newer DirectX version (12 Ultimate (12_2)) and a newer Vulkan version (1.4) compared to the K40c’s DirectX 12 (11_0) and Vulkan 1.2.175. The RTX 2070 also has a significantly higher boost clock of 1620 MHz versus the K40c’s 876 MHz, and supports modern GDDR6 memory, whereas the K40c uses older GDDR5.

Head-to-Head Benchmarks

The sole head-to-head benchmark in the data is Geekbench OpenCL. The results are lopsided. The RTX 2070 scores 79,966, while the Tesla K40c scores 17,468. This translates to a 357.8% performance advantage for the RTX 2070, meaning it is nearly 4.6 times faster in this specific compute test. This massive delta is a direct consequence of the architectural improvements, higher clock speeds, and greater memory bandwidth of the RTX 2070.

There are no other common benchmarks available for a direct comparison. The RTX 2070 has a broad suite of Passmark tests and 3DMark results, but the K40c’s benchmark data is limited to just the Geekbench OpenCL score. This lack of overlap makes it impossible to compare them in DirectX 9, 10, 11, or 12 workloads, or in G2D/G3D performance. The data is clear: in the only measurable common workload, the RTX 2070 is the overwhelming victor, and the K40c’s 61st percentile ranking among all GPUs is far below the RTX 2070’s 63rd percentile.

FAQ

Q: Is the NVIDIA Tesla K40c faster than the RTX 2070 in any way?

A: Based on the provided data, no. The RTX 2070 wins the only benchmark they share, Geekbench OpenCL, with a score of 79,966 versus 17,468. The K40c does have a larger memory capacity (12 GB vs 8 GB), but this does not translate to a performance win in the available data.

Q: Which GPU has more shading units?

A: The Tesla K40c has more shading units, with 2,880 compared to the RTX 2070’s 2,304. However, the RTX 2070’s much higher clocks and newer architecture lead to far superior real-world performance.

Q: Can the Tesla K40c be used for gaming?

A: The data does not support this use case. The K40c has no display outputs, making it impossible to connect a monitor directly. While it could theoretically render frames, they would have to be passed to another device. Its old DirectX 12 (11_0) support and lack of RT and tensor cores also make it unsuitable for modern games.

Q: What is the key advantage of the RTX 2070's memory?

A: The RTX 2070 uses GDDR6 memory with a bandwidth of 448.0 GB/s, which is significantly faster than the K40c’s GDDR5 memory at 288.4 GB/s. This higher bandwidth is crucial for feeding the RTX 2070’s faster processor and enabling higher frame rates and compute throughput.

Q: Which card has a higher launch MSRP?

A: The NVIDIA Tesla K40c had a launch MSRP of 7,699 USD, which is considerably higher than the RTX 2070’s launch MSRP of 499 USD. This reflects the K40c’s positioning as a professional compute card at the time of its release.

Q: Does the K40c's larger memory size make it better for AI workloads?

A: While the K40c has 12 GB of memory, the RTX 2070 has dedicated tensor cores that are specifically designed for AI and deep learning tasks. The K40c has no such hardware. The RTX 2070’s tensor cores, combined with its massive compute lead, make it the better choice for AI workloads, despite the K40c’s memory capacity advantage.

Where Each One Wins

NVIDIA GeForce RTX 2070: This card wins decisively in almost every measurable category. It is the clear choice for compute-heavy OpenCL workloads, as evidenced by its 357.8% lead in Geekbench OpenCL. Its support for DirectX 12 Ultimate (12_2) and Vulkan 1.4 makes it the only viable option for modern gaming and graphical applications. The presence of RT cores and tensor cores gives it a unique capability for ray-traced rendering and AI-accelerated features, which the K40c cannot match. Its higher pixel rate (103.7 GPixel/s vs 52.56 GPixel/s) and texture rate (233.3 GTexel/s vs 210.2 GTexel/s) also indicate superior rasterization performance. The RTX 2070 is the all-around winner for any task that values speed, modern features, and API compatibility.

NVIDIA Tesla K40c: The K40c’s only theoretical advantage lies in its 12 GB memory capacity, which is 4 GB more than the RTX 2070. This could be a deciding factor for specific legacy compute workloads that require loading very large datasets into VRAM. However, this advantage is purely capacity-based; the K40c’s memory bandwidth is lower (288.4 GB/s vs 448.0 GB/s). Its higher transistor count in shading units (2,880) is irrelevant given its much lower clocks and older architecture. The data shows that the K40c wins in no benchmark and offers no performance advantage. Its only potential use case is a niche scenario where the 12 GB memory pool is mandatory and the user is willing to accept a massive performance penalty.

Specification Differences

The following table highlights the key specification differences between the two GPUs, based on the provided data.

| Specification | NVIDIA GeForce RTX 2070 | NVIDIA Tesla K40c |

| :--- | :--- | :--- |

| Architecture | Turing | Kepler |

| Process Node | 12 nm | 28 nm |

| Transistors | 10,800 million | 7,080 million |

| Die Size | 445 mm² | 561 mm² |

| Base Clock | 1410 MHz | 745 MHz |

| Boost Clock | 1620 MHz | 876 MHz |

| Memory Size | 8 GB | 12 GB |

| Memory Type | GDDR6 | GDDR5 |

| Memory Bus Width | 256 bit | 384 bit |

| Memory Bandwidth | 448.0 GB/s | 288.4 GB/s |

| Shading Units | 2304 | 2880 |

| TMUs | 144 | 240 |

| ROPs | 64 | 48 |

| RT Cores | 36 | null |

| Tensor Cores | 288 | null |

| Pixel Rate | 103.7 GPixel/s | 52.56 GPixel/s |

| Texture Rate | 233.3 GTexel/s | 210.2 GTexel/s |

| FP32 Performance | 7.465 TFLOPS | 5.046 TFLOPS |

| TDP | 175 W | 245 W |

| Power Connectors | 1x 8-pin | 1x 6-pin + 1x 8-pin |

| Suggested PSU | 450 W | 550 W |

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

| Vulkan Support | 1.4 | 1.2.175 |

| Display Outputs | 1x DVI, 1x HDMI 2.0, 2x DisplayPort 1.4a, 1x USB Type-C | No outputs |

| Length | 229 mm | 267 mm |