NVIDIA GeForce RTX 4070 SUPER vs NVIDIA Tesla M40 24 GB Comparison

The NVIDIA GeForce RTX 4070 SUPER and the NVIDIA Tesla M40 24 GB represent two distinct eras of GPU design, separated by nearly a decade of architectural evolution. The data shows a clear generational gap, with the RTX 4070 SUPER dominating in every benchmark category where both were tested. However, the Tesla M40’s 24 GB memory capacity and its specific compute-oriented design make it a unique piece of hardware that still holds relevance in specific workflows, despite its older Maxwell architecture.

Where Each One Wins

The benchmark results provide a stark picture of performance disparity, but the wins are not distributed evenly across all possible workloads. In the two head-to-head tests available—Geekbench OpenCL and Geekbench Vulkan—the RTX 4070 SUPER is the unequivocal winner. The Geekbench OpenCL score of 172,795 for the RTX 4070 SUPER dwarfs the Tesla M40’s 37,439, representing a 361.5% advantage. Similarly, in Geekbench Vulkan, the RTX 4070 SUPER scores 205,624 versus the Tesla M40’s 45,975, a 347.3% lead. These are not marginal victories; they are orders-of-magnitude improvements in raw compute throughput.

The Tesla M40, however, wins in a category that the benchmark suite does not directly measure: memory capacity. With 24 GB of GDDR5 memory on a 384-bit bus, it offers double the memory of the RTX 4070 SUPER’s 12 GB. This is a significant advantage for workloads that are capacity-bound rather than compute-bound, such as large dataset processing or certain scientific simulations that require fitting an entire model into VRAM. The data shows the RTX 4070 SUPER has a bandwidth of 504.2 GB/s, which is higher than the M40’s 288.4 GB/s, but the sheer capacity of the M40 remains its primary winning attribute.

Furthermore, the RTX 4070 SUPER’s feature set extends beyond raw compute. It includes 56 RT cores and 224 Tensor cores, enabling hardware-accelerated ray tracing and AI workloads, which the Tesla M40 lacks entirely (its rtCores and tensorCores fields are null). While the benchmark data does not include ray-tracing tests, the presence of these dedicated hardware units means the RTX 4070 SUPER is the clear winner for any modern graphics or AI-accelerated task.

Architecture Differences

The architectural gulf between these two GPUs is the root cause of their performance disparity. The RTX 4070 SUPER is built on the Ada Lovelace architecture using TSMC’s 5 nm process node, while the Tesla M40 uses the Maxwell 2.0 architecture on a 28 nm process. This process shrink is monumental: the RTX 4070 SUPER packs 35,800 million transistors into a 294 mm² die, achieving a transistor density of 121.8 million transistors per square millimeter. In contrast, the Tesla M40 has 8,000 million transistors on a much larger 601 mm² die, resulting in a density of just 13.3 million transistors per square millimeter. This explains the massive efficiency and performance gap.

The core configurations reflect this generational leap. The RTX 4070 SUPER has 7,168 shading units, 224 texture mapping units (TMUs), and 80 render output units (ROPs). The Tesla M40 has 3,072 shading units, 192 TMUs, and 96 ROPs. While the M40 has more ROPs, the RTX 4070 SUPER more than doubles the shading units and has a higher texture fill rate of 554.4 GTexel/s versus the M40’s 213.5 GTexel/s. The pixel rate also favors the newer card: 198.0 GPixel/s versus 106.8 GPixel/s.

Clock speeds tell a similar story. The RTX 4070 SUPER has a base clock of 1980 MHz and a boost clock of 2475 MHz, while the Tesla M40 operates at a base of 948 MHz and a boost of 1112 MHz. Combined with the architecture improvements, this results in a FP32 compute performance of 35.48 TFLOPS for the RTX 4070 SUPER versus 6.832 TFLOPS for the Tesla M40. The RTX 4070 SUPER also supports FP16 at a 1:1 ratio, while the M40 has no listed FP16 capability. The memory subsystem differs as well: the RTX 4070 SUPER uses 12 GB of GDDR6X on a 192-bit bus, while the M40 uses 24 GB of GDDR5 on a 384-bit bus.

Head-to-Head Benchmarks

The available head-to-head data is limited to two tests, but the results are decisive. In Geekbench OpenCL, the RTX 4070 SUPER scores 172,795 against the Tesla M40’s 37,439. This is a 361.5% delta, meaning the RTX 4070 SUPER is roughly 4.6 times faster in this compute-oriented API test. The Geekbench Vulkan test shows a similar pattern: the RTX 4070 SUPER scores 205,624 versus the M40’s 45,975, a 347.3% delta, or about 4.5 times faster.

These deltas are consistent with the theoretical compute specifications. The RTX 4070 SUPER’s FP32 throughput of 35.48 TFLOPS is over five times the M40’s 6.832 TFLOPS, and the actual benchmark deltas slightly trail that theoretical maximum, likely due to API overhead and memory bandwidth constraints. However, the results are unambiguous: the RTX 4070 SUPER wins both head-to-head tests, and the margin is overwhelming.

Looking at the broader benchmark context, the RTX 4070 SUPER has an average benchmark score of 43,223 across all its tested workloads, placing it at the 83rd percentile of all GPUs. Its nearest rivals include the NVIDIA Quadro M6000 24 GB (average score 43,262, delta -0.1%) and the NVIDIA GeForce RTX 4090 Mobile (average score 43,667, delta -1%). The Tesla M40, in contrast, has an average benchmark score of 41,707, also at the 83rd percentile, with rivals like the NVIDIA GeForce RTX 3080 Ti (average score 41,187, delta 1.3%) and the AMD Radeon RX 7650 GRE (average score 42,723, delta -2.4%). This indicates that while the M40 is not slow in an absolute sense, it is competing with a different class of hardware than the RTX 4070 SUPER.

FAQ

Q: Is the RTX 4070 SUPER always faster than the Tesla M40 in compute benchmarks?

A: Yes, in the two head-to-head tests available (Geekbench OpenCL and Vulkan), the RTX 4070 SUPER wins by margins of 361.5% and 347.3% respectively.

Q: Does the Tesla M40 have any advantage over the RTX 4070 SUPER?

A: The Tesla M40 has a memory capacity advantage of 24 GB versus 12 GB, which is beneficial for workloads that require large datasets to be resident in VRAM, even though its bandwidth is lower at 288.4 GB/s versus 504.2 GB/s.

Q: Which GPU has more shading units?

A: The RTX 4070 SUPER has 7,168 shading units, while the Tesla M40 has 3,072, giving the newer card more than double the raw shader count.

Q: Are there any ray tracing or AI capabilities on the Tesla M40?

A: No, the Tesla M40 has no RT cores or Tensor cores listed, whereas the RTX 4070 SUPER includes 56 RT cores and 224 Tensor cores.

Q: Which card is more power-hungry?

A: The Tesla M40 has a higher TDP of 250 W compared to the RTX 4070 SUPER’s 220 W, despite the latter delivering significantly more performance.

Q: What are the process node differences?

A: The RTX 4070 SUPER uses a 5 nm process, while the Tesla M40 uses a 28 nm process, leading to vastly different transistor densities of 121.8M / mm² versus 13.3M / mm².

The Verdict

The data leads to a straightforward conclusion: the NVIDIA GeForce RTX 4070 SUPER is the superior GPU for virtually any compute or graphics workload. Its FP32 performance of 35.48 TFLOPS is more than five times that of the Tesla M40, and its benchmark scores reflect this, with a 361.5% lead in OpenCL and a 347.3% lead in Vulkan. It also brings modern features like ray tracing and tensor cores, which the M40 cannot offer. The RTX 4070 SUPER is the clear pick for gaming, content creation, AI inference, and any application that benefits from the latest architectural advancements.

The Tesla M40 24 GB, however, is not without its niche. Its 24 GB of memory is a significant asset for specific professional workloads where capacity is the bottleneck. For example, if a user needs to load a massive model or dataset that exceeds 12 GB, the M40 becomes a viable option, even if it is slower in raw compute. Its average benchmark score of 41,707 is respectable, and it sits at the 83rd percentile, showing it is not obsolete in all contexts. The data suggests that the M40 is a compute-oriented card for legacy scientific or visualization tasks that require large memory footprints, while the RTX 4070 SUPER is a general-purpose powerhouse that excels in almost every measurable way.

Specification Differences

The following table highlights only the fields where the two GPUs differ, based on the provided data:

| Specification | NVIDIA GeForce RTX 4070 SUPER | NVIDIA Tesla M40 24 GB |

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

| Architecture | Ada Lovelace | Maxwell 2.0 |

| Process Node | 5 nm | 28 nm |

| Transistors | 35,800 million | 8,000 million |

| Die Size | 294 mm² | 601 mm² |

| Transistor Density | 121.8M / mm² | 13.3M / mm² |

| Base Clock | 1980 MHz | 948 MHz |

| Boost Clock | 2475 MHz | 1112 MHz |

| Memory Clock | 1313 MHz 21 Gbps effective | 1502 MHz 6 Gbps effective |

| Memory Size | 12 GB | 24 GB |

| Memory Type | GDDR6X | GDDR5 |

| Memory Bus Width | 192 bit | 384 bit |

| Memory Bandwidth | 504.2 GB/s | 288.4 GB/s |

| Shading Units | 7168 | 3072 |

| TMUs | 224 | 192 |

| ROPs | 80 | 96 |

| RT Cores | 56 | null |

| Tensor Cores | 224 | null |

| Pixel Rate | 198.0 GPixel/s | 106.8 GPixel/s |

| Texture Rate | 554.4 GTexel/s | 213.5 GTexel/s |

| FP32 Compute | 35.48 TFLOPS | 6.832 TFLOPS |

| FP16 Compute | 35.48 TFLOPS (1:1) | null |

| TDP | 220 W | 250 W |

| Power Connectors | 1x 16-pin | 8-pin EPS |

| Suggested PSU | 550 W | 600 W |

| Bus Interface | PCIe 4.0 x16 | PCIe 3.0 x16 |

| Display Outputs | 1x HDMI 2.1, 3x DisplayPort 1.4a | No outputs |

| DirectX Support | 12 Ultimate (12_2) | 12 (12_1) |

| Release Date | 2024-01-16 | 2015-11-09 |

| Predecessor | GeForce 30 | Tesla Kepler |

| Successor | GeForce 50 | Tesla Pascal |

| Launch MSRP | 599 USD | null |