AMD Radeon AI PRO R9700S vs NVIDIA H20 Comparison

Head-to-Head Benchmarks

The recorded database contains no direct benchmark scores for either the AMD Radeon AI PRO R9700S or the NVIDIA H20. Both entries show an empty benchmark array, an average benchmark score of zero, and a percentile rank of 50 against all GPUs. With no measured performance data, a traditional head-to-head comparison of application performance cannot be constructed from the available facts. What can be compared directly are the architectural capabilities, memory subsystems, compute throughput figures, and physical specifications that define each product's theoretical ceiling.

The raw compute figures show a split decision. The AMD Radeon AI PRO R9700S delivers 47.84 TFLOPS of FP32 performance and the same 47.84 TFLOPS of FP16 performance at a 1:1 ratio. The NVIDIA H20 delivers 39.54 TFLOPS of FP32 but scales to 79.07 TFLOPS of FP16 at a 2:1 ratio. In FP32 workloads, the AMD part holds a 8.30 TFLOPS advantage, which translates to roughly 21% higher raw single-precision throughput. In FP16 workloads, the NVIDIA part reverses the outcome with a 31.23 TFLOPS lead, or approximately 65% higher half-precision throughput. These figures indicate that the Radeon AI PRO R9700S favors general compute and graphics-style FP32 pipelines, while the H20 is structured for mixed-precision AI training and inference where FP16 dominates.

Memory bandwidth presents a similarly distinct picture. The NVIDIA H20 carries 96 GB of HBM3 on a 6144-bit bus, producing 4.03 TB/s of bandwidth. The AMD Radeon AI PRO R9700S uses 32 GB of GDDR6 on a 256-bit bus, yielding 644.6 GB/s. The H20's bandwidth is approximately 6.25 times higher, a margin that directly impacts large model training, data movement, and memory-bound inference tasks. The AMD card compensates with lower power draw, 300 W versus 500 W, and a smaller physical footprint at 267 mm length, 109 mm height, and 39 mm width, compared to the H20's SXM module format, which has no recorded dimensions.

FAQ

Q: Which GPU has higher FP32 compute throughput?

A: The AMD Radeon AI PRO R9700S delivers 47.84 TFLOPS of FP32, compared to 39.54 TFLOPS for the NVIDIA H20. The AMD part is ahead by 8.30 TFLOPS, approximately 21% higher.

Q: Which GPU offers more memory capacity?

A: The NVIDIA H20 provides 96 GB of HBM3 memory. The AMD Radeon AI PRO R9700S provides 32 GB of GDDR6. The H20 has three times the capacity.

Q: What is the memory bandwidth difference?

A: The NVIDIA H20 reaches 4.03 TB/s over a 6144-bit bus. The AMD Radeon AI PRO R9700S reaches 644.6 GB/s over a 256-bit bus. The H20's bandwidth is roughly 6.25 times higher.

Q: Do both cards support PCIe 5.0?

A: Yes, both the AMD Radeon AI PRO R9700S and the NVIDIA H20 use a PCIe 5.0 x16 bus interface.

Q: What are the display output options?

A: The AMD Radeon AI PRO R9700S includes 4x DisplayPort 2.1a outputs. The NVIDIA H20 has no display outputs.

Q: Which card has a higher transistor count?

A: The NVIDIA H20 contains 80,000 million transistors on an 814 mm² die. The AMD Radeon AI PRO R9700S contains 53,900 million transistors on a 357 mm² die. The H20 has roughly 48% more transistors, but the AMD chip achieves a higher transistor density of 151.0M per mm² versus 98.3M per mm².

Where Each One Wins

The AMD Radeon AI PRO R9700S wins in scenarios that prioritize raw FP32 throughput, display connectivity, and power efficiency. Its 47.84 TFLOPS of FP32 makes it the stronger candidate for traditional graphics workloads, scientific visualization, and compute tasks that rely on single-precision arithmetic. The 4x DisplayPort 2.1a outputs allow direct connection to multiple monitors, which suits workstation environments. The 300 W power draw, alongside a suggested PSU of 700 W, positions it as a more manageable deployment for air-cooled, dual-slot PCIe installations. The RDNA 4.0 architecture with 4096 shading units, 256 TMUs, 128 ROPs, and 64 RT cores gives it a conventional GPU feature set, including DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4 support.

The NVIDIA H20 wins in memory-heavy AI workloads and mixed-precision computing. Its 96 GB of HBM3 with 4.03 TB/s bandwidth provides a massive capacity and throughput advantage for large language models, training batches, and inference serving. The 79.07 TFLOPS of FP16 nearly doubles its own FP32 output and exceeds the AMD part's FP16 by 31.23 TFLOPS, making it the better fit for half-precision neural network training. The 312 tensor cores are a dedicated resource for matrix operations, a feature the AMD card lacks entirely. The 9984 shading units and 312 TMUs contribute to a high raw instruction throughput, while the 24 ROPs limit pixel output to 47.52 GPixel/s, which matters less in a server compute context. The SXM module form factor and 500 W power draw, with a suggested PSU of 900 W, indicate a data center-oriented design with no video outputs.

Specification Differences

The two cards differ across nearly every major specification category. The AMD Radeon AI PRO R9700S uses the Navi 48 chip on RDNA 4.0 architecture, built on a 4 nm TSMC process. The NVIDIA H20 uses the GH100 chip on Hopper architecture, built on a 5 nm TSMC process. The AMD chip has 53,900 million transistors on a 357 mm² die, while the NVIDIA chip has 80,000 million transistors on an 814 mm² die. Transistor density favors AMD at 151.0M per mm² versus 98.3M per mm².

Clock speeds differ substantially. The AMD card runs at 1660 MHz base, 2920 MHz boost, and 2350 MHz game clock, with memory at 2518 MHz or 20.1 Gbps effective. The NVIDIA card runs at 1830 MHz base and 1980 MHz boost, with memory at 1313 MHz or 5.3 Gbps effective. Memory configurations are entirely different: AMD uses 32 GB GDDR6 on a 256-bit bus for 644.6 GB/s; NVIDIA uses 96 GB HBM3 on a 6144-bit bus for 4.03 TB/s.

Compute unit counts diverge. AMD has 4096 shading units, 256 TMUs, 128 ROPs, and 64 RT cores, with no tensor cores. NVIDIA has 9984 shading units, 312 TMUs, 24 ROPs, no RT cores, and 312 tensor cores. Pixel rate favors AMD at 373.8 GPixel/s versus 47.52 GPixel/s. Texture rate favors AMD at 747.5 GTexel/s versus 617.8 GTexel/s.

Power and physical design differ. AMD draws 300 W with a 700 W suggested PSU, uses a dual-slot form factor, a 16-pin power connector, and measures 267 mm by 109 mm by 39 mm. NVIDIA draws 500 W with a 900 W suggested PSU, uses an SXM module, has no power connector listed, and has no recorded dimensions. AMD offers 4x DisplayPort 2.1a; NVIDIA offers no display outputs. AMD supports DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4; NVIDIA lists N/A for all three APIs.

Architecture Differences

The AMD Radeon AI PRO R9700S is built on RDNA 4.0, a graphics-first architecture that maintains a 1:1 FP16 to FP32 ratio, meaning half-precision operations do not receive a throughput multiplier. Its 64 RT cores provide dedicated ray tracing acceleration, and the 4096 shading units are organized around a unified shader design. The 4 nm process allows a high transistor density of 151.0M per mm², which contributes to the relatively compact 357 mm² die. The card's 256-bit GDDR6 memory interface prioritizes latency and simplicity over raw bandwidth, and the presence of DisplayPort 2.1a outputs confirms a workstation graphics orientation.

The NVIDIA H20 is built on Hopper, a server-oriented architecture that emphasizes tensor operations and mixed-precision compute. Its 312 tensor cores are the centerpiece, designed to accelerate matrix multiplication for AI workloads. The FP16 throughput of 79.07 TFLOPS at a 2:1 ratio over FP32 indicates a deliberate doubling of half-precision capability. The 9984 shading units provide a large general-purpose compute array, but the 24 ROPs and 47.52 GPixel/s pixel rate show that rasterization is not a priority. The 5 nm process yields a lower transistor density of 98.3M per mm² on a much larger 814 mm² die. The 6144-bit HBM3 interface delivers 4.03 TB/s, which is the defining architectural feature for feeding large datasets into the compute units. The SXM module form factor and lack of display outputs confirm a headless data center deployment model.

The release timeline also differs: the AMD card was released on 2025-12-10, while the NVIDIA card was released on 2024-01-31. The AMD card's predecessor is listed as Radeon Pro Vega, while the NVIDIA card's predecessor is Server Ada and its successor is Server Blackwell. Both are marked as Active in production status.

The Verdict

The data indicates two different products for two different job profiles. The AMD Radeon AI PRO R9700S is the appropriate choice for workloads that rely on FP32 compute, graphics rendering, and direct display output. Its 47.84 TFLOPS of FP32, 373.8 GPixel/s pixel rate, and 747.5 GTexel/s texture rate, combined with 64 RT cores and full DirectX 12 Ultimate support, make it a functional workstation GPU. The 300 W power draw and dual-slot 267 mm length allow integration into standard PCIe workstations. The lack of tensor cores and the 1:1 FP16 ratio mean it is not optimized for AI training, but its 32 GB GDDR6 memory is sufficient for large visual datasets and single-precision simulation.

The NVIDIA H20 is the appropriate choice for AI server deployments where memory capacity and bandwidth are critical. Its 96 GB HBM3 and 4.03 TB/s bandwidth provide the data throughput needed for large model training and inference. The 79.07 TFLOPS of FP16 and 312 tensor cores give it a decisive advantage in half-precision AI workloads. The 500 W power draw and SXM module form factor require a server chassis with appropriate cooling, and the absence of display outputs means it is not intended for any graphics output role. The 39.54 TFLOPS of FP32 is lower than the AMD part, but that is secondary for the H20's intended compute domain.

The choice comes down to workload type. For interactive graphics, visualization, and FP32-heavy compute with display needs, the AMD Radeon AI PRO R9700S delivers higher single-precision throughput at lower power. For memory-bound AI training and inference with FP16 precision, the NVIDIA H20 delivers over six times the memory bandwidth and over 65% more FP16 throughput. The 21% FP32 advantage for AMD and the 65% FP16 advantage for NVIDIA are the two headline numbers that separate these products.