NVIDIA A100 PCIe 40 GB vs NVIDIA RTX 4000 SFF Ada Generation Comparison

The NVIDIA A100 PCIe 40 GB and the NVIDIA RTX 4000 SFF Ada Generation occupy opposite ends of the workstation and server spectrum. The A100 is a server-oriented Ampere part with a massive memory bus and compute focus, while the RTX 4000 SFF is a compact Ada Lovelace workstation card designed for efficiency and display output. Benchmark results place the A100 decisively ahead in raw compute, but the data also reveals a distinct set of strengths for the RTX 4000 that go beyond raw performance.

Where Each One Wins

The performance split is clear-cut in the available benchmark data. The A100 PCIe 40 GB wins both head-to-head tests, taking the Geekbench OpenCL and Vulkan scores with substantial margins. Its average benchmark score of 162,504 places it in the 97th percentile of all GPUs, while the RTX 4000 SFF Ada Generation averages 117,088, sitting in the 95th percentile. This means the A100 is not just faster in these tests; it is positioned among the top 3% of all graphics cards, whereas the RTX 4000 is in the top 5%.

Looking at the nearest rivals confirms the A100’s standing. Its average score is 1.1% ahead of the AMD Radeon Pro W6800X and 1.4% behind the AMD Radeon PRO W7800, placing it in a tight cluster of high-end workstation cards. The RTX 4000, by contrast, is nearly tied with the NVIDIA GB10 (0.3% behind) and 1.6% behind the AMD Radeon PRO W7700, indicating it competes in a lower performance tier. The RTX 4000 does have a niche: it is 2.4% ahead of the Tesla V100 SXM2 16 GB and 2.8% ahead of the RTX A5500 Mobile, showing it beats some older or mobile parts.

The A100’s wins are not marginal. In OpenCL, it scores 178,627 against 124,812 for the RTX 4000, a 43.1% advantage. In Vulkan, the gap narrows slightly but remains significant: 146,380 versus 109,364, a 33.8% lead. The RTX 4000 does not win any of the two head-to-head tests, but its lower power and physical footprint are qualitative advantages that the benchmark scores do not capture.

Architecture Differences

The two GPUs are built on different architectures and process nodes. The A100 uses the GA100 chip on TSMC’s 7 nm process, while the RTX 4000 uses the AD104 chip on a 5 nm node. The A100’s die is substantially larger at 826 mm², housing 54,200 million transistors, which yields a transistor density of 65.6 million per mm². The RTX 4000’s die is 294 mm² with 35,800 million transistors, achieving a much higher density of 121.8 million per mm². This density advantage reflects the newer manufacturing process.

Memory architecture is a major differentiator. The A100 features 40 GB of HBM2e on a 5120-bit bus, delivering 1.56 TB/s of bandwidth. The RTX 4000 has 20 GB of GDDR6 on a 160-bit bus, with 280.0 GB/s of bandwidth. The A100’s bandwidth is over five times higher, which is critical for data-intensive workloads. The memory clock also differs: the A100 runs at 1215 MHz (2.4 Gbps effective), while the RTX 4000 runs at 1750 MHz (14 Gbps effective), but the wider bus of the A100 dominates.

Compute resources tell a similar story. The A100 has 6912 shading units, 432 TMUs, 160 ROPs, and 432 tensor cores. The RTX 4000 has 6144 shading units, 192 TMUs, 64 ROPs, 48 ray tracing cores, and 192 tensor cores. The A100 lacks dedicated ray tracing cores, while the RTX 4000 includes them. The A100’s FP32 throughput is 19.49 TFLOPS, slightly ahead of the RTX 4000’s 19.17 TFLOPS. However, the FP16 figures are dramatically different: the A100 reaches 77.97 TFLOPS with a 4:1 ratio, while the RTX 4000 achieves 19.17 TFLOPS at a 1:1 ratio. This suggests the A100 is optimized for mixed-precision AI workloads.

The physical and power profiles diverge sharply. The A100 has a 250 W TDP with an 8-pin EPS connector and a suggested 600 W power supply. It is a dual-slot card measuring 267 mm in length. The RTX 4000 has a 70 W TDP, requires no power connectors, and suggests a 250 W power supply. It is also dual-slot but much shorter at 168 mm. The RTX 4000 has four mini-DisplayPort 1.4a outputs, while the A100 has no display outputs. The A100 is end-of-life with a 2020 release date, while the RTX 4000 is active, released in 2023.

Head-to-Head Benchmarks

The Geekbench OpenCL test shows the largest gap. The A100 scores 178,627, which is 43.1% higher than the RTX 4000’s 124,812. This is a substantial win that likely reflects the A100’s superior memory bandwidth and higher shading unit count. The RTX 4000’s lower score places it well below the A100’s nearest rivals, as the A100’s delta of 1.1% over the W6800X shows it is competitive with the top of its class.

The Vulkan test narrows the gap but still favors the A100. The A100 scores 146,380, which is 33.8% ahead of the RTX 4000’s 109,364. The smaller delta in Vulkan compared to OpenCL may indicate that the RTX 4000’s newer architecture handles the API more efficiently, but it still cannot overcome the raw compute deficit. The RTX 4000’s Vulkan score is close to its average benchmark score, whereas the A100’s Vulkan score is below its OpenCL result, suggesting the A100 has API-specific strengths.

The average benchmark scores reinforce the head-to-head results. The A100’s average of 162,504 is 38.8% higher than the RTX 4000’s 117,088. The A100’s percentile rank of 97 versus the RTX 4000’s 95 shows that while both are high performers, the A100 sits in a more exclusive tier. The nearest rival data for the RTX 4000 shows it is just 0.3% behind the GB10 and 2.4% ahead of the V100 SXM2, meaning it is firmly in the mid-to-high range but not at the top.

FAQ

Q: Which GPU has higher raw compute performance in the benchmarks?

A: The NVIDIA A100 PCIe 40 GB wins both head-to-head tests. It scores 178,627 in OpenCL and 146,380 in Vulkan, compared to 124,812 and 109,364 for the RTX 4000 SFF Ada Generation.

Q: How large is the performance gap between the two?

A: The A100 leads by 43.1% in OpenCL and 33.8% in Vulkan. Its average benchmark score of 162,504 is roughly 38.8% higher than the RTX 4000’s 117,088.

Q: Does the RTX 4000 have any advantages in the data?

A: Yes, it has a much lower TDP of 70 W versus 250 W, requires no power connectors, and includes display outputs. It also has a higher transistor density of 121.8M per mm² versus 65.6M per mm².

Q: How do the memory systems compare?

A: The A100 has 40 GB of HBM2e with a 5120-bit bus and 1.56 TB/s bandwidth. The RTX 4000 has 20 GB of GDDR6 with a 160-bit bus and 280.0 GB/s bandwidth.

Q: Are these GPUs from the same generation?

A: No. The A100 is from the Server Ampere generation with a GA100 chip, while the RTX 4000 is from the Workstation Ada generation with an AD104 chip.

Q: Which GPU has better ray tracing capabilities?

A: The RTX 4000 has 48 dedicated ray tracing cores, while the A100 lists no ray tracing cores in its specifications.

The Verdict

The data points to a clear choice for compute-heavy workloads: the NVIDIA A100 PCIe 40 GB. It wins both benchmark tests by over 30%, has a 97th percentile ranking, and offers over five times the memory bandwidth of the RTX 4000. Its 77.97 TFLOPS FP16 performance is particularly notable for AI and scientific computing, where the RTX 4000’s 19.17 TFLOPS falls far short. For users who need maximum throughput and have the power budget, the A100 is the superior option.

The RTX 4000 SFF Ada Generation is the pick for different reasons. Its 70 W TDP, lack of power connectors, and compact size make it suitable for constrained environments. The presence of four mini-DisplayPort outputs and dedicated ray tracing cores adds versatility for professional visualization. Its 95th percentile ranking is respectable, and its 20 GB of GDDR6 memory is ample for many tasks, but it trails the A100 by 33.8% to 43.1% in the benchmarks. Users who prioritize efficiency, physical space, and display connectivity over peak compute should choose the RTX 4000.

Specification Differences

| Specification | NVIDIA A100 PCIe 40 GB | NVIDIA RTX 4000 SFF Ada Generation |

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

| Architecture | Ampere | Ada Lovelace |

| Generation | Server Ampere (Axx) | Workstation Ada (x000A) |

| Process Node | 7 nm | 5 nm |

| Transistors | 54,200 million | 35,800 million |

| Die Size | 826 mm² | 294 mm² |

| Transistor Density | 65.6M / mm² | 121.8M / mm² |

| Base Clock | 765 MHz | 720 MHz |

| Boost Clock | 1410 MHz | 1560 MHz |

| Memory Size | 40 GB | 20 GB |

| Memory Type | HBM2e | GDDR6 |

| Memory Bus | 5120 bit | 160 bit |

| Memory Bandwidth | 1.56 TB/s | 280.0 GB/s |

| Shading Units | 6912 | 6144 |

| TMUs | 432 | 192 |

| ROPs | 160 | 64 |

| Ray Tracing Cores | None | 48 |

| Tensor Cores | 432 | 192 |

| FP32 Performance | 19.49 TFLOPS | 19.17 TFLOPS |

| FP16 Performance | 77.97 TFLOPS (4:1) | 19.17 TFLOPS (1:1) |

| TDP | 250 W | 70 W |

| Power Connectors | 8-pin EPS | None |

| Suggested PSU | 600 W | 250 W |

| Display Outputs | No outputs | 4x mini-DisplayPort 1.4a |

| Length | 267 mm | 168 mm |

| Height | 111 mm | 69 mm |

| Production Status | End-of-life | Active |

| Release Date | 2020-06-21 | 2023-03-20 |