NVIDIA A100 SXM4 40 GB vs NVIDIA GeForce RTX 4090 D Comparison

NVIDIA’s A100 SXM4 40 GB and GeForce RTX 4090 D represent two very different philosophies in GPU design, separated by three years of architectural evolution and aimed at entirely different workloads. The A100 is a server-focused compute accelerator built for massive parallel throughput and memory capacity, while the RTX 4090 D is a desktop-oriented graphics card that leverages the newer Ada Lovelace architecture for both raw speed and modern rendering features. The benchmark data shows a clear split: the RTX 4090 D dominates the two measurable synthetic tests, yet the A100 holds a higher average benchmark score across all recorded tests, illustrating how aggregate metrics can obscure per-workload behavior.

FAQ

Q: Which GPU has the higher average benchmark score?

A: The NVIDIA A100 SXM4 40 GB leads with an average benchmark score of 187,147, compared to 178,050 for the GeForce RTX 4090 D. This places the A100 4.9% ahead of the RTX 4090 D in the nearestRivals comparison.

Q: How does the RTX 4090 D perform in Geekbench OpenCL relative to the A100?

A: The RTX 4090 D scores 278,621 in Geekbench OpenCL, which is 27.8% higher than the A100’s 201,096. This is the single largest margin of victory in the head-to-head data.

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

A: The A100 uses 40 GB of HBM2e memory on a 5120-bit bus, delivering 1.56 TB/s of bandwidth. The RTX 4090 D has 24 GB of GDDR6X on a 384-bit bus, providing 1.01 TB/s.

Q: Which GPU has a higher transistor density?

A: The RTX 4090 D, built on a 5 nm process, achieves 125.3 million transistors per mm². The A100, on a 7 nm node, has a density of 65.6 million transistors per mm².

Q: Are both GPUs considered end-of-life products?

A: Yes, both the NVIDIA A100 SXM4 40 GB and the GeForce RTX 4090 D have a production status of "End-of-life" in the data.

Q: What is the TDP difference between the two cards?

A: The A100 has a TDP of 400 W, while the RTX 4090 D draws slightly more at 425 W. Both have a suggested PSU rating of 800 W.

Architecture Differences

The two GPUs are built on different manufacturing processes and architectural generations. The A100 uses the GA100 chip on a 7 nm TSMC process, part of the Ampere architecture, with a die size of 826 mm² housing 54,200 million transistors. In contrast, the RTX 4090 D uses the AD102 chip on a 5 nm TSMC node, featuring the Ada Lovelace architecture, with a smaller 609 mm² die but a much higher transistor count of 76,300 million. This translates to a transistor density of 65.6 million per mm² for the A100 versus 125.3 million per mm² for the RTX 4090 D, indicating a significantly more compact and dense design for the newer card.

Core configurations differ substantially. The A100 has 6,912 shading units, 432 TMUs, 160 ROPs, and 432 tensor cores, but notably lacks dedicated RT cores. The RTX 4090 D, meanwhile, packs 14,592 shading units, 456 TMUs, 176 ROPs, 456 tensor cores, and 114 RT cores. The presence of RT cores in the RTX 4090 D enables hardware-accelerated ray tracing, a feature entirely absent from the A100’s specification sheet. Memory architecture also diverges: the A100 employs 40 GB of HBM2e with a 5120-bit bus and 1.56 TB/s bandwidth, while the RTX 4090 D uses 24 GB of GDDR6X with a 384-bit bus and 1.01 TB/s bandwidth.

Clock speeds and compute rates further separate the two. The A100 operates at a base clock of 1095 MHz and boosts to 1410 MHz, delivering 19.49 TFLOPS of FP32 and 77.97 TFLOPS of FP16 (with a 4:1 ratio). The RTX 4090 D runs at a 2280 MHz base and 2520 MHz boost, producing 73.54 TFLOPS of FP32 and 73.54 TFLOPS of FP16 at a 1:1 ratio. This means the RTX 4090 D has roughly 3.8 times the FP32 throughput of the A100, but the A100 has a higher FP16 peak when its 4:1 mode is active. The A100 is a single-slot SXM module with no display outputs or power connectors, while the RTX 4090 D is a triple-slot card with a 16-pin connector, HDMI 2.1, and three DisplayPort 1.4a outputs.

Head-to-Head Benchmarks

The head-to-head data provides two direct comparisons, both favoring the RTX 4090 D decisively. In Geekbench OpenCL, the RTX 4090 D scores 278,621 against the A100’s 201,096, a delta of -27.8% (meaning the A100 trails by that percentage). This is a substantial margin, reflecting the RTX 4090 D’s advantage in raw FP32 compute and its higher boost clocks. The A100’s 19.49 TFLOPS FP32 output is clearly outmatched in this general-purpose compute test, even with its HBM2e memory bandwidth advantage.

The Geekbench Vulkan test shows an even larger gap. The RTX 4090 D scores 246,941, while the A100 manages 173,198, resulting in a delta of -29.9% for the A100. This near-30% deficit highlights the RTX 4090 D’s superior graphics and rasterization capabilities, supported by its 443.5 GPixel/s pixel rate and 1,149.1 GTexel/s texture rate versus the A100’s 225.6 GPixel/s and 609.1 GTexel/s. The A100’s lack of dedicated RT cores and modern API support (no DirectX, OpenGL, or Vulkan listed) puts it at a clear disadvantage in graphics-oriented workloads, even though it remains competitive in the aggregate.

Overall, the RTX 4090 D wins 2 out of 2 head-to-head benchmarks. However, it is noteworthy that the A100 still achieves a higher average benchmark score (187,147 vs. 178,050) and holds a positive deltaPct of 1.3% against the RTX 5000 Ada Generation, while the RTX 4090 D shows a -2.2% delta against the same rival. This suggests that the A100’s strengths lie in workloads not captured by these two synthetic tests, likely memory-bound or FP16-intensive tasks.

Specification Differences

The two cards differ across nearly every specification field. Process node: A100 uses 7 nm, RTX 4090 D uses 5 nm. Die size: 826 mm² versus 609 mm². Transistors: 54,200 million versus 76,300 million. Transistor density: 65.6M/mm² versus 125.3M/mm². Base clock: 1095 MHz versus 2280 MHz. Boost clock: 1410 MHz versus 2520 MHz. Memory clock: 1215 MHz (2.4 Gbps effective) versus 1313 MHz (21 Gbps effective). Memory size: 40 GB versus 24 GB. Memory type: HBM2e versus GDDR6X. Bus width: 5120-bit versus 384-bit. Bandwidth: 1.56 TB/s versus 1.01 TB/s.

Shading units: 6,912 versus 14,592. TMUs: 432 versus 456. ROPs: 160 versus 176. RT cores: none versus 114. Tensor cores: 432 versus 456. Pixel rate: 225.6 GPixel/s versus 443.5 GPixel/s. Texture rate: 609.1 GTexel/s versus 1,149.1 GTexel/s. FP32: 19.49 TFLOPS versus 73.54 TFLOPS. FP16: 77.97 TFLOPS (4:1) versus 73.54 TFLOPS (1:1). TDP: 400 W versus 425 W. Slot width: SXM Module versus Triple-slot. Power connectors: none versus 1x 16-pin. Display outputs: none versus 1x HDMI 2.1, 3x DisplayPort 1.4a. API support: the A100 lists no DirectX, OpenGL, or Vulkan versions, while the RTX 4090 D supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. Release dates: 2020-05-13 versus 2023-12-27.

Where Each One Wins

The RTX 4090 D is the clear winner for graphics-intensive and general compute tasks that leverage modern APIs and high FP32 throughput. Its 73.54 TFLOPS FP32 performance is nearly four times the A100’s 19.49 TFLOPS, and its Vulkan score of 246,941 versus 173,198 demonstrates a 29.9% advantage in graphics-centric rendering. The presence of 114 RT cores, DirectX 12 Ultimate support, and display outputs makes it a fully-featured consumer GPU suitable for gaming, 3D rendering, and workstation tasks. Its higher pixel and texture rates (443.5 GPixel/s and 1,149.1 GTexel/s) further cement its position for rasterization-heavy workloads.

The A100, despite losing both head-to-head benchmarks, wins on aggregate metrics and memory capacity. Its 40 GB of HBM2e with 1.56 TB/s bandwidth is 55% higher bandwidth than the RTX 4090 D’s 1.01 TB/s, making it superior for memory-bound compute tasks like large model inference or scientific simulations. Its FP16 peak of 77.97 TFLOPS (4:1) slightly exceeds the RTX 4090 D’s 73.54 TFLOPS, giving it an edge in mixed-precision AI workloads when the 4:1 mode is fully utilized. The A100’s higher average benchmark score (187,147) and its positive deltaPct of 1.3% against the RTX 5000 Ada Generation indicate that its strengths lie outside the tested metrics, likely in areas where memory bandwidth and capacity dominate.

In summary, the RTX 4090 D is the better choice for real-time graphics, gaming, and FP32-centric compute, while the A100 excels in large-scale data processing, AI training with FP16, and scenarios demanding high memory bandwidth and capacity. The RTX 4090 D also carries a launch MSRP of 1,599 USD, though no comparable pricing exists for the A100 in the data.