AMD Radeon PRO W7900 vs NVIDIA GeForce RTX 4090 D Comparison

NVIDIA's GeForce RTX 4090 D and AMD's Radeon PRO W7900 are both 99th-percentile GPUs, but they target different corners of the professional market. The data shows a clear performance hierarchy in the shared benchmark suite, yet the AMD card counters with a massive memory capacity advantage that defines its use case. This analysis breaks down the head-to-head results, architectural divergence, and the specific workloads where each card justifies its existence.

Head-to-Head Benchmarks

The GeForce RTX 4090 D dominates the two benchmarks both cards share, and the margin is not subtle. In Geekbench OpenCL, the NVIDIA card scores 271,315 against the Radeon PRO W7900's 195,048, a 39.1% advantage. That is a decisive lead in a compute-oriented API that stresses raw shader throughput and driver efficiency. The gap widens dramatically in Geekbench Vulkan, where the RTX 4090 D posts 244,421 versus 137,070 for the AMD card, a 78.3% delta. This near-doubling of performance suggests NVIDIA's Vulkan implementation is substantially more mature or that the architecture's scheduling handles the workload far more efficiently.

Looking at the aggregate averages, the RTX 4090 D holds a 5.2% lead over the Radeon PRO W7900 in the database's composite score — 174,774 versus 166,059. The NVIDIA card also sits 8.5% above the RTX A5500 and 4.5% below the RTX 4500 Ada Generation, placing it in a tight cluster of high-end workstation parts. The AMD card, meanwhile, is just 3.1% ahead of the RTX A5500 and 3.8% ahead of the Radeon Pro W6900X, indicating it barely edges out last-generation competition despite its newer architecture. The 3DMark Steel Nomad DX12 test appears only for the NVIDIA card, where it scores 8,587; no comparable data exists for the AMD side, leaving DirectX 12 gaming-style performance unquantified for the Radeon PRO W7900.

Architecture Differences

The two GPUs are built on the same 5 nm TSMC process, but their internal designs could not be more different. NVIDIA's AD102 chip packs 76,300 million transistors into a 609 mm² die, yielding a transistor density of 125.3M per mm². AMD's Navi 31, codenamed Plum Bonito, contains 57,700 million transistors on a 529 mm² die, with a density of 109.1M per mm². NVIDIA's chip is physically larger and denser, which translates into a raw resource advantage across nearly every compute unit category.

The RTX 4090 D deploys 14,592 shading units, 456 texture mapping units, and 176 ROPs, alongside 114 RT cores and 456 tensor cores. The Radeon PRO W7900 counters with 6,144 shading units, 384 TMUs, 192 ROPs, and 96 RT cores, but has no tensor core equivalent — a critical omission for AI and deep learning workloads. This 2.4x difference in shading units explains the rasterization and compute gap, even though AMD's higher ROP count (192 versus 176) helps pixel throughput. Clock speeds partially close the gap: the NVIDIA card boosts to 2520 MHz from a 2280 MHz base, while AMD boosts to 2495 MHz from 1855 MHz. The result is that NVIDIA achieves 73.54 TFLOPS of FP32 performance and 73.54 TFLOPS of FP16 (1:1), while AMD manages 61.32 TFLOPS FP32 but doubles to 122.6 TFLOPS FP16 (2:1) — a notable advantage for AMD in half-precision compute.

Memory is where the strategic split becomes obvious. The RTX 4090 D ships with 24 GB of GDDR6X on a 384-bit bus, delivering 1.01 TB/s of bandwidth. The Radeon PRO W7900 doubles capacity to 48 GB of GDDR6 on the same 384-bit bus, but bandwidth drops to 864.0 GB/s due to slower 18 Gbps effective memory speed versus NVIDIA's 21 Gbps. The AMD card's 864 GB/s is still substantial, but the 1.01 TB/s on the NVIDIA side provides a 17% bandwidth advantage for memory-heavy rendering tasks. Power draw reflects the performance disparity: the RTX 4090 D is rated at 425 W with a recommended 800 W PSU, while the Radeon PRO W7900 sips 295 W and needs only a 600 W PSU. Both cards occupy triple-slot cooling solutions, with the NVIDIA unit slightly larger at 304 mm long versus AMD's 280 mm.

Where Each One Wins

The RTX 4090 D wins every benchmark where both cards have data. In OpenCL, its 39.1% lead indicates a commanding advantage in general-purpose GPU compute, which covers physics simulations, rendering, and scientific workloads that rely on OpenCL. The Vulkan result is even more lopsided — 78.3% ahead — making it the clear choice for real-time visualization, game engines, and any application that leverages Vulkan for compute or graphics. The NVIDIA card's tensor cores (456 of them) also give it an unquantified but architecturally obvious edge in AI inference and training, which the Radeon PRO W7900 cannot match due to its lack of tensor hardware.

The Radeon PRO W7900's victory condition is capacity, not speed. Its 48 GB of VRAM is exactly double the RTX 4090 D's 24 GB, and that extra memory is the deciding factor for datasets that exceed 24 GB. Large language model inference, massive 3D scenes, complex scientific visualizations, and multi-application workflows that need to hold several GPU-resident datasets simultaneously will run on the AMD card where the NVIDIA card would fail due to insufficient memory. The AMD card also offers a 2:1 FP16 ratio, delivering 122.6 TFLOPS — 67% more than NVIDIA's 73.54 TFLOPS FP16 — for workloads that can exploit half-precision arithmetic, such as certain machine learning training loops and image processing pipelines. Additionally, the Radeon's lower 295 W TDP and 600 W PSU recommendation make it easier to integrate into existing workstations without major power infrastructure changes.

The Verdict

Choose the NVIDIA GeForce RTX 4090 D if raw compute throughput is the priority. The data shows it is 39.1% faster in OpenCL and 78.3% faster in Vulkan than the Radeon PRO W7900, and its aggregate benchmark score is 5.2% higher. It is the superior card for GPU-bound rendering, real-time graphics, and any compute task that fits within 24 GB of memory. The 456 tensor cores provide an architectural path for AI workloads that the AMD card simply lacks. This is the card for developers and artists who need maximum speed per frame or per iteration and do not exceed the memory ceiling.

Choose the AMD Radeon PRO W7900 if memory capacity is non-negotiable. At 48 GB, it offers double the RTX 4090 D's VRAM, which is the only way to handle workloads that spill past 24 GB — a hard wall that no amount of compute power can overcome. The 122.6 TFLOPS FP16 performance also makes it competitive for half-precision tasks, and its 295 W power draw is significantly lighter on the system. It is the card for researchers loading large models, VFX artists working with massive textures, and analysts processing oversized datasets. Its benchmark deficits — 39.1% in OpenCL and 78.3% in Vulkan — are real, but they do not matter if the alternative cannot fit the working set.

FAQ

Q: Which GPU has a higher average benchmark score?

A: The NVIDIA GeForce RTX 4090 D has an average benchmark score of 174,774, which is 5.2% higher than the AMD Radeon PRO W7900's 166,059.

Q: How much faster is the RTX 4090 D in Vulkan compared to the Radeon PRO W7900?

A: The RTX 4090 D scores 244,421 in Geekbench Vulkan versus 137,070 for the Radeon PRO W7900, a 78.3% advantage for NVIDIA.

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

A: The AMD Radeon PRO W7900 has 48 GB of GDDR6 memory, exactly double the 24 GB of GDDR6X found on the NVIDIA GeForce RTX 4090 D.

Q: Does the Radeon PRO W7900 have any compute advantage over the RTX 4090 D?

A: Yes, in FP16 (half-precision) compute the Radeon PRO W7900 delivers 122.6 TFLOPS, compared to 73.54 TFLOPS on the RTX 4090 D, due to its 2:1 FP16 ratio versus NVIDIA's 1:1.

Q: Which card has a higher memory bandwidth?

A: The NVIDIA GeForce RTX 4090 D has 1.01 TB/s of bandwidth, which is 17% higher than the Radeon PRO W7900's 864.0 GB/s.

Q: What are the TDP requirements for each card?

A: The RTX 4090 D is rated at 425 W and requires an 800 W power supply, while the Radeon PRO W7900 is rated at 295 W and recommends a 600 W PSU.