AMD Ryzen Z2 GPU vs NVIDIA H100 CNX Comparison

Head-to-Head Benchmarks

The recorded data shows no direct head-to-head benchmark entries between the AMD Ryzen Z2 GPU and the NVIDIA H100 CNX. Both products sit at the 50th percentile in the database, but this is a neutral placement that reflects the absence of measured comparisons rather than parity in actual performance. The AMD Ryzen Z2 GPU has an average benchmark score of zero, and the NVIDIA H100 CNX also records an average benchmark score of zero. No wins are logged for either side in the head-to-head table, so the direct comparison must be drawn from the architectural and specification data available in the database.

The AMD Ryzen Z2 GPU delivers 8.294 TFLOPS of FP32 compute, while the NVIDIA H100 CNX delivers 53.84 TFLOPS. That is a substantial gap, roughly 6.5 times higher on the NVIDIA side in raw single-precision throughput. In FP16 workloads, the divergence becomes even more extreme. The NVIDIA H100 CNX reaches 215.4 TFLOPS with a 4:1 ratio, whereas the AMD Ryzen Z2 GPU achieves 8.294 TFLOPS with a 1:1 ratio. The NVIDIA part is built around tensor core throughput, and the data reflects that focus clearly. The AMD chip does not list tensor cores at all, while the NVIDIA H100 CNX includes 456 tensor cores. For machine learning inference or training tasks that rely on FP16 and tensor operations, the numerical advantage is overwhelming.

Memory bandwidth tells a similar story. The NVIDIA H100 CNX uses 80 GB of HBM2e on a 5120-bit bus, producing 2.04 TB/s of bandwidth. The AMD Ryzen Z2 GPU uses 16 GB of LPDDR5X on a 128-bit bus, producing 119.9 GB/s. That is a 17-fold difference in memory bandwidth. The NVIDIA part moves data at a rate that the AMD chip cannot approach, which matters for large matrix operations, model weights, and data-intensive server workloads. The AMD part has a smaller memory pool and a narrower bus, but its 16 GB capacity is still substantial for a 28 W part in a console or handheld context.

Pixel fill rates invert the expected pattern. The AMD Ryzen Z2 GPU records 86.40 GPixel/s, while the NVIDIA H100 CNX records 44.28 GPixel/s. The AMD chip has 32 ROPs compared to the NVIDIA part's 24 ROPs, and its higher boost clock of 2700 MHz versus 1845 MHz helps push pixel throughput higher. Texture rate also favors the NVIDIA part heavily: the H100 CNX reaches 841.3 GTexel/s, while the AMD chip reaches 129.6 GTexel/s. The NVIDIA part has 456 TMUs, while the AMD part has 48. The AMD chip wins the pixel race, but the NVIDIA chip dominates texture work.

The AMD Ryzen Z2 GPU boosts to 2700 MHz, while the NVIDIA H100 CNX boosts to 1845 MHz. Base clocks are closer, with the AMD part at 800 MHz and the NVIDIA part at 690 MHz. The AMD chip runs at a much lower power envelope, 28 W versus 350 W, which explains the clock advantage. The NVIDIA part uses roughly 12.5 times the power, but it converts that into a massively wider execution engine.

The Verdict

The data splits along clear workload lines. The AMD Ryzen Z2 GPU is a 28 W, 4 nm part with 25,390 million transistors on a 178 mm² die. It uses RDNA 3.0 architecture, supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4, and includes 768 shading units, 48 TMUs, 32 ROPs, and 12 RT cores. Its 16 GB of LPDDR5X memory and 119.9 GB/s bandwidth fit a low-power client device. The NVIDIA H100 CNX is a 350 W, 5 nm server part with 80,000 million transistors on an 814 mm² die. It uses Hopper architecture, has no display outputs, no listed graphics API support, and includes 14,592 shading units, 456 TMUs, 24 ROPs, and 456 tensor cores. Its 80 GB of HBM2e memory and 2.04 TB/s bandwidth target data center acceleration.

The verdict from the data is straightforward. For graphics rendering on a power-limited client platform, the AMD Ryzen Z2 GPU holds the edge in pixel rate, offers RT cores, and runs within a 28 W envelope. For compute-heavy server workloads, especially those using FP16 or tensor operations, the NVIDIA H100 CNX is in a different class. The 215.4 TFLOPS FP16 figure and 456 tensor cores position it firmly for AI and HPC tasks. No benchmark scores exist to bridge these two designs, so the separation is defined by architecture intent, not measured results.

FAQ

Q: Which GPU has higher FP32 compute?

A: The NVIDIA H100 CNX records 53.84 TFLOPS FP32, while the AMD Ryzen Z2 GPU records 8.294 TFLOPS FP32.

Q: How much memory bandwidth does each GPU provide?

A: The NVIDIA H100 CNX provides 2.04 TB/s from 80 GB of HBM2e on a 5120-bit bus. The AMD Ryzen Z2 GPU provides 119.9 GB/s from 16 GB of LPDDR5X on a 128-bit bus.

Q: Does the AMD Ryzen Z2 GPU support ray tracing?

A: Yes, the database lists 12 RT cores for the AMD Ryzen Z2 GPU. The NVIDIA H100 CNX has no RT core count listed.

Q: Which GPU has a higher boost clock?

A: The AMD Ryzen Z2 GPU boosts to 2700 MHz. The NVIDIA H100 CNX boosts to 1845 MHz.

Q: What process nodes are used?

A: The AMD Ryzen Z2 GPU uses a 4 nm TSMC process. The NVIDIA H100 CNX uses a 5 nm TSMC process.

Q: Which GPU includes tensor cores?

A: The NVIDIA H100 CNX includes 456 tensor cores. The AMD Ryzen Z2 GPU does not list any tensor cores.

Specification Differences

The two GPUs differ across nearly every measurable field. The AMD Ryzen Z2 GPU uses a 4 nm process node, while the NVIDIA H100 CNX uses 5 nm. Transistor counts diverge sharply: the AMD part has 25,390 million transistors, the NVIDIA part has 80,000 million. Die size also differs, with the AMD chip at 178 mm² and the NVIDIA chip at 814 mm². Transistor density favors the AMD part at 142.6 million transistors per mm² versus 98.3 million for the NVIDIA part.

Base clocks sit at 800 MHz for the AMD chip and 690 MHz for the NVIDIA chip. Boost clocks reach 2700 MHz on the AMD side and 1845 MHz on the NVIDIA side. The AMD part lists no memory clock value beyond 937 MHz with 7.5 Gbps effective, while the NVIDIA part runs at 1593 MHz with 3.2 Gbps effective. Memory size differs at 16 GB versus 80 GB. Memory type differs as LPDDR5X versus HBM2e. Bus width differs at 128 bit versus 5120 bit. Bandwidth differs at 119.9 GB/s versus 2.04 TB/s.

Shading units number 768 on the AMD chip versus 14,592 on the NVIDIA chip. TMUs number 48 versus 456. ROPs number 32 versus 24. RT cores are present on the AMD chip at 12, while the NVIDIA chip lists none. Tensor cores are absent on the AMD chip, while the NVIDIA chip lists 456. Pixel rate favors the AMD chip at 86.40 GPixel/s versus 44.28 GPixel/s. Texture rate favors the NVIDIA chip at 841.3 GTexel/s versus 129.6 GTexel/s. FP32 output favors the NVIDIA chip at 53.84 TFLOPS versus 8.294 TFLOPS. FP16 output favors the NVIDIA chip at 215.4 TFLOPS versus 8.294 TFLOPS.

Power consumption differs at 28 W for the AMD part and 350 W for the NVIDIA part. The NVIDIA part is dual-slot, uses an 8-pin EPS connector, and suggests a 750 W PSU. The AMD part has no slot width listed, no power connectors, and no suggested PSU. The NVIDIA part uses PCIe 5.0 x16, while the AMD part has no bus interface listed. Display outputs differ: the AMD part has 1x USB Type-C, the NVIDIA part has no outputs. The AMD part supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. The NVIDIA part lists no graphics API support. The NVIDIA part measures 267 mm in length and 111 mm in height. The AMD part has no dimensions listed.

Architecture Differences

The AMD Ryzen Z2 GPU is built on the Hawk Point chip and uses RDNA 3.0 architecture. It belongs to the Console GPU generation from AMD. The NVIDIA H100 CNX is built on the GH100 chip and uses Hopper architecture. It belongs to the Server Hopper generation from NVIDIA. The two designs target completely different execution models.

The AMD part has 12 RT cores, which indicates hardware support for ray tracing workloads. It also lists DirectX 12 Ultimate support, which confirms a graphics-oriented feature set. The NVIDIA part has no RT core count and no graphics API entries. Instead, it carries 456 tensor cores, which indicates a design optimized for matrix math and neural network operations. The FP16 ratio confirms this: the NVIDIA part runs FP16 at 4:1 relative to FP32, a common configuration for tensor-heavy accelerators. The AMD part runs FP16 at 1:1, which means it treats FP16 and FP32 as equally weighted operations.

Memory architecture also separates the two. The AMD part uses LPDDR5X, a low-power memory type suited to client devices. The NVIDIA part uses HBM2e, a high-bandwidth stacked memory type suited to server accelerators. The bus width difference, 128 bit versus 5120 bit, reflects the fundamental design split. The AMD part is designed to fit within a 28 W envelope and a small die. The NVIDIA part is designed to fill a dual-slot server card with a 350 W power draw and a 750 W suggested PSU.

The AMD part has a higher transistor density at 142.6 million per mm², which reflects the denser 4 nm process. The NVIDIA part has a lower density at 98.3 million per mm² despite having more than three times the total transistors. The larger die on the NVIDIA side allows for massive shading unit and tensor core counts, but it also requires more power and cooling. The AMD part compensates with a smaller die, a lower power draw, and a higher boost clock.

Display output support also differs. The AMD part includes 1x USB Type-C, which allows it to drive a display directly. The NVIDIA part has no display outputs, which confirms it is not intended for direct graphics output. The release dates differ as well: the AMD part launched on 2024-12-31, while the NVIDIA part launched on 2023-03-20. The NVIDIA part lists its predecessor as Server Ada and its successor as Server Blackwell. The AMD part has no predecessor or successor listed.

Where Each One Wins

The AMD Ryzen Z2 GPU wins in pixel fill rate, with 86.40 GPixel/s versus 44.28 GPixel/s for the NVIDIA H100 CNX. It also wins in raw clock speed, with a 2700 MHz boost versus 1845 MHz. It wins in power efficiency in the sense that it operates at 28 W, a fraction of the NVIDIA part's 350 W. It has RT cores, which the NVIDIA part lacks, and it supports DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4. It includes a display output, while the NVIDIA part has none. For a compact, low-power graphics device that needs to render frames and output video, the AMD part holds the relevant advantages.

The NVIDIA H100 CNX wins in shading units, with 14,592 versus 768. It wins in TMUs, with 456 versus 48. It wins in tensor cores, with 456 versus none. It wins in FP32 throughput, with 53.84 TFLOPS versus 8.294 TFLOPS. It wins in FP16 throughput, with 215.4 TFLOPS versus 8.294 TFLOPS. It wins in texture rate, with 841.3 GTexel/s versus 129.6 GTexel/s. It wins in memory capacity, bandwidth, and bus width. It wins in transistor count and die size. For server-side compute, AI inference, and large-scale data processing, the NVIDIA part is the clear choice.

The recorded data does not include any benchmark matches between these two products, so the win split is derived entirely from the specification fields. The AMD part is a graphics processor with ray tracing, API support, and a display output. The NVIDIA part is a compute accelerator with tensor cores and enormous memory bandwidth. Each one wins where its architecture is designed to operate.