AMD Radeon AI PRO 9600D vs NVIDIA RTX 4500 Ada Generation Comparison

Where Each One Wins

The recorded data splits cleanly by workload type and generation. The AMD Radeon AI PRO 9600D is the newer product, built on RDNA 4.0 and released later in the product cycle, while the NVIDIA RTX 4500 Ada Generation is an established workstation card from the Ada Lovelace line. Benchmark results indicate the AMD card targets capacity and efficiency, while the NVIDIA card targets raw compute throughput and rendering speed.

The NVIDIA RTX 4500 Ada Generation holds a decisive advantage in peak compute performance. Its FP32 throughput of 39.63 TFLOPS is significantly higher than the AMD card’s 24.82 TFLOPS, a 59.7% lead. Texture rate follows the same pattern: 619.2 GTexel/s versus 387.8 GTexel/s, a 59.6% advantage. These numbers point to the NVIDIA card winning in compute-heavy tasks like simulation, rendering, and general GPU compute workloads where raw shader throughput dominates.

The AMD Radeon AI PRO 9600D counters with memory capacity and bandwidth efficiency. It offers 32 GB of GDDR6 memory on a 256-bit bus, delivering 576.0 GB/s of bandwidth. The NVIDIA card provides 24 GB on a 192-bit bus, yielding 432.0 GB/s. That is a 33.3% capacity advantage and a 33.3% bandwidth advantage for AMD. For workloads that fit within 24 GB, the NVIDIA card’s higher compute rate wins. For datasets that exceed 24 GB, the AMD card avoids spills or partitioning, which can outweigh raw compute differences.

The AMD card also wins on power efficiency per the stated TDP. Its 150 W TDP is 28.6% lower than the NVIDIA card’s 210 W. The AMD card is single-slot, while the NVIDIA card requires dual-slot cooling. The AMD card also uses PCIe 5.0 x16, while the NVIDIA card uses PCIe 4.0 x16. These factors favor the AMD card in dense workstation builds or systems with strict power and space budgets.

FAQ

Q: Which card has more memory and bandwidth?

A: The AMD Radeon AI PRO 9600D has 32 GB of GDDR6 memory with a 256-bit bus, producing 576.0 GB/s bandwidth. The NVIDIA RTX 4500 Ada Generation has 24 GB with a 192-bit bus, producing 432.0 GB/s.

Q: Which card has higher raw compute performance?

A: The NVIDIA RTX 4500 Ada Generation leads in FP32 at 39.63 TFLOPS versus 24.82 TFLOPS for the AMD card. Texture rate is 619.2 GTexel/s versus 387.8 GTexel/s.

Q: What are the power consumption differences?

A: The AMD card has a 150 W TDP and a suggested PSU of 450 W. The NVIDIA card has a 210 W TDP and a suggested PSU of 550 W.

Q: Which card supports newer PCIe technology?

A: The AMD card uses PCIe 5.0 x16, while the NVIDIA card uses PCIe 4.0 x16.

Q: What display outputs does each card provide?

A: The AMD card has 1x DisplayPort 2.1a. The NVIDIA card has 4x DisplayPort 1.4a.

Q: How do the cards compare in the database benchmark percentile?

A: The NVIDIA card is at the 97th percentile across all GPUs, with an average benchmark score of 166,094. The AMD card has no recorded benchmark scores and sits at the 50th percentile.

Head-to-Head Benchmarks

The database contains no direct head-to-head benchmark entries for these two cards, so the comparison relies on published specification-based performance metrics and the NVIDIA card’s recorded benchmark results.

The NVIDIA RTX 4500 Ada Generation shows its strength in the Geekbench records. It scores 160,786 in OpenCL and 171,401 in Vulkan, with an average benchmark score of 166,094. That average places it at the 97th percentile of all GPUs. Its nearest rivals include the NVIDIA RTX A5500 with an average score of 165,217, a 0.5% difference; the AMD Radeon PRO W7800 at 164,894, a 0.7% difference; the AMD Radeon Pro W6900X at 168,574, a -1.5% difference; and the NVIDIA A100 PCIe 40 GB at 162,504, a 2.2% difference. These margins show the RTX 4500 Ada Generation is tightly clustered with other high-end workstation cards, neither clearly ahead nor behind its immediate peers.

For the AMD Radeon AI PRO 9600D, the absence of benchmark entries means the database records no score and no rival comparisons. The analysis must therefore rely on its architectural and specification data. The AMD card’s FP32 throughput of 24.82 TFLOPS is 37.4% lower than the NVIDIA card’s 39.63 TFLOPS. The pixel rate is close, 193.9 GPixel/s versus 206.4 GPixel/s, a 6.1% deficit for AMD. Texture rate is the largest gap, 387.8 GTexel/s versus 619.2 GTexel/s.

The AMD card does win on memory metrics. Its 32 GB capacity is 33.3% higher, and its 576.0 GB/s bandwidth is 33.3% higher. The AMD card also has a larger transistor count, 53,900 million versus 45,900 million, and a smaller die, 357 mm² versus 379 mm², resulting in a higher transistor density of 151.0M per mm² versus 121.1M per mm². These factors suggest the AMD card uses its transistor budget for memory subsystem and density, while the NVIDIA card uses its budget for compute units.

Specification Differences

The two cards differ across nearly every measured specification. The AMD card uses 3072 shading units, while the NVIDIA card uses 7680, a 2.5x difference. TMUs are 192 versus 240, a 25% advantage for NVIDIA. ROPs are 96 versus 80, a 20% advantage for AMD. Ray tracing cores: the AMD card has 48, the NVIDIA card has 60, a 25% advantage for NVIDIA. Tensor cores: the AMD card has none, the NVIDIA card has 240. The AMD card has no tensor core count listed, which indicates a fundamental architectural difference in AI acceleration.

Clock speeds also differ. The AMD card has a base clock of 1080 MHz and a boost clock of 2020 MHz. The NVIDIA card has a base clock of 2070 MHz and a boost clock of 2580 MHz. The NVIDIA card’s base clock is 91.7% higher, and its boost clock is 27.7% higher. Memory clocks are identical at 2250 MHz with 18 Gbps effective, but the bus widths differ, 256-bit versus 192-bit, producing the bandwidth gap.

Power and physical dimensions differ. The AMD card has a TDP of 150 W and uses a 1x 16-pin power connector. The NVIDIA card has a TDP of 210 W and lists no power connectors, implying it draws power through the PCIe slot or uses a different connector scheme not recorded. The AMD card is single-slot, 241 mm long, 111 mm tall, and 19 mm wide. The NVIDIA card is dual-slot, 245 mm long, 112 mm tall, with no recorded width. The AMD card suggests a 450 W PSU, the NVIDIA card suggests a 550 W PSU.

Bus interface and display outputs differ. The AMD card uses PCIe 5.0 x16 and one DisplayPort 2.1a output. The NVIDIA card uses PCIe 4.0 x16 and four DisplayPort 1.4a outputs. Both support DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4.

Architecture Differences

The AMD Radeon AI PRO 9600D is built on the RDNA 4.0 architecture using the Navi 48 chip, fabricated on a 4 nm process at TSMC. It is part of the Radeon Pro Navi (Navi IV Series) generation, released later, and its predecessor is the Radeon Pro Vega. The chip contains 53,900 million transistors on a 357 mm² die, yielding a transistor density of 151.0M per mm². The architecture provides 48 ray tracing cores but no tensor cores, meaning AI and machine learning workloads rely on standard shader execution or external libraries rather than dedicated tensor hardware.

The NVIDIA RTX 4500 Ada Generation is built on the Ada Lovelace architecture using the AD103 chip, fabricated on a 5 nm process at TSMC. It belongs to the GeForce 40-series and the Workstation Ada generation. Its predecessor is Workstation Ampere, and its successor is Blackwell PRO W. The chip contains 45,900 million transistors on a 379 mm² die, yielding a transistor density of 121.1M per mm². The architecture provides 60 ray tracing cores and 240 tensor cores, giving it dedicated hardware for ray tracing and AI acceleration.

The process node difference, 4 nm versus 5 nm, gives the AMD card a smaller feature size and higher transistor density. The AMD card’s transistor count is 17.4% higher, yet its die is 5.8% smaller, confirming a denser layout. The NVIDIA card compensates with a much higher shader core count, 7680 versus 3072, and a higher clock speed, which explains its compute advantage despite fewer transistors.

The absence of tensor cores on the AMD card is the most significant architectural divide. Any AI workload that leverages NVIDIA’s tensor cores, such as deep learning inference or training, will see a substantial advantage on the NVIDIA card. The AMD card must rely on its 3072 shading units for such tasks, which limits its AI throughput relative to the NVIDIA card’s 240 tensor cores.

The Verdict

The data indicates two distinct design philosophies. The NVIDIA RTX 4500 Ada Generation is the compute leader. Its FP32 throughput of 39.63 TFLOPS, texture rate of 619.2 GTexel/s, and 240 tensor cores make it the stronger choice for rendering, simulation, and AI-accelerated workloads that can utilize tensor hardware. Its 97th percentile ranking, with an average benchmark score of 166,094, confirms it performs at the top tier among all GPUs.

The AMD Radeon AI PRO 9600D is the capacity and efficiency leader. Its 32 GB memory and 576.0 GB/s bandwidth exceed the NVIDIA card by 33.3% in both metrics. Its 150 W TDP is 28.6% lower, and its single-slot design with PCIe 5.0 support fits into smaller or more power-constrained systems. For workloads that need to hold large datasets in memory, such as certain scientific visualization or large model inference scenarios, the AMD card avoids the capacity ceiling of 24 GB.

The benchmark gap is decisive on paper. The NVIDIA card’s compute rates are roughly 60% higher in FP32 and texture throughput, and its tensor cores provide dedicated AI acceleration that the AMD card lacks entirely. The AMD card’s advantages are in memory capacity, bandwidth, power draw, and physical footprint. No recorded benchmark data exists for the AMD card, so its real-world performance remains unverified in the database, while the NVIDIA card has solid benchmark entries.

For users prioritizing raw compute speed, ray tracing, or tensor-based AI, the NVIDIA RTX 4500 Ada Generation is the data-backed choice. For users prioritizing memory capacity, bandwidth efficiency, lower power draw, and single-slot installation, the AMD Radeon AI PRO 9600D offers clear specification advantages. The choice depends on whether the workload is compute-bound or memory-bound. The data supports the NVIDIA card for compute-bound tasks and the AMD card for memory-bound tasks with strict power or space constraints.