AMD Ryzen Z2 GPU vs NVIDIA Jetson Orin Nano Super Comparison

Head-to-Head Benchmarks

The recorded database contains no direct head-to-head benchmark scores for the AMD Ryzen Z2 GPU and the NVIDIA Jetson Orin Nano Super. Both parts sit at the 50th percentile in the overall GPU distribution, and both carry an average benchmark score of zero in the current records. This absence of measured data means any comparative performance claims must be derived from the architectural specifications and theoretical throughput figures listed in the database, not from actual workload results.

The most striking numerical gap appears in raw shader throughput. The AMD Ryzen Z2 GPU delivers 8.294 TFLOPS of FP32 compute, which is approximately 3.97 times the 2.089 TFLOPS offered by the NVIDIA Jetson Orin Nano Super. That factor of nearly four in single-precision floating-point performance suggests a substantial advantage for the AMD part in any workload that scales directly with shader count and clock frequency. The AMD chip sustains a boost clock of 2700 MHz across 768 shading units, while the NVIDIA chip's shading units (1024 total) operate at unspecified clocks, making a direct per-clock comparison impossible from the available data.

In FP16 throughput, the relationship flips in terms of ratio, though the AMD part still holds the absolute lead. The Ryzen Z2 GPU achieves 8.294 TFLOPS in FP16 with a 1:1 ratio to FP32, meaning it does not gain any extra throughput by reducing precision. The Jetson Orin Nano Super achieves 4.178 TFLOPS in FP16 with a 2:1 ratio, effectively doubling its FP32 rate. Even with that doubling, the NVIDIA part reaches only about half the AMD part's FP16 output. The AMD advantage in FP16 remains roughly 1.98 times, a smaller gap than in FP32 but still decisive.

Pixel and texture throughput tell a similar story. The Ryzen Z2 GPU generates 86.40 GPixel/s against the Jetson's 16.32 GPixel/s, a 5.29 times advantage in pixel fill rate. Texture rate shows 129.6 GTexel/s for AMD versus 32.64 GTexel/s for NVIDIA, a 3.97 times gap that mirrors the FP32 ratio. These figures derive from the combination of clock speeds, ROP counts (32 versus 16), and TMU counts (48 versus 32). The AMD part's higher clocks amplify its larger ROP count, while the NVIDIA part's higher TMU count relative to its ROPs does not compensate for the clock deficit.

Memory bandwidth provides the closest contest between the two. The Ryzen Z2 GPU accesses 16 GB of LPDDR5X across a 128-bit bus at 7.5 Gbps effective, yielding 119.9 GB/s. The Jetson Orin Nano Super accesses 8 GB of LPDDR5 across the same 128-bit bus at 6.4 Gbps effective, yielding 102.4 GB/s. The AMD part leads by 17.5 GB/s, a 17.1 percent advantage. This narrower gap suggests that memory-bound workloads will show less disparity than compute-bound ones, though the AMD part still holds the lead.

Architecture Differences

The two processors come from different manufacturers, different foundries, and different architectural generations. The AMD Ryzen Z2 GPU uses the Hawk Point chip with RDNA 3.0 architecture, built on a 4 nm process at TSMC. The NVIDIA Jetson Orin Nano Super uses the GA10B chip with Ampere architecture, built on an 8 nm process at Samsung. The process node difference is substantial: 4 nm versus 8 nm represents a full generation gap in lithography, which typically affects power efficiency and transistor density.

Transistor counts cannot be compared directly because the database records 25,390 million transistors for the AMD chip and an unknown figure for the NVIDIA chip. The AMD die size is 178 mm², while the NVIDIA die size is 200 mm². The AMD transistor density calculates to 142.6 million transistors per square millimeter; no density figure exists for the NVIDIA part. The AMD chip packs more transistors into a smaller area, consistent with its more advanced process node.

Memory architecture differs in type and capacity. The Ryzen Z2 GPU uses LPDDR5X, a newer standard than the LPDDR5 used by the Jetson Orin Nano Super. Both run at 128-bit bus widths, but the AMD part's memory clock of 937 MHz (7.5 Gbps effective) exceeds the NVIDIA part's 800 MHz (6.4 Gbps effective). The AMD part carries 16 GB versus 8 GB, doubling the capacity for data residency.

Compute resource allocation diverges significantly. The AMD part deploys 768 shading units, 48 texture mapping units, 32 raster output units, and 12 ray tracing cores, with no tensor cores listed. The NVIDIA part deploys 1024 shading units, 32 TMUs, 16 ROPs, and 32 tensor cores, with no ray tracing cores listed. The NVIDIA design favors more parallel shader lanes and dedicated tensor hardware, while the AMD design favors fewer but faster shader units plus dedicated ray tracing acceleration.

Tensor cores represent the clearest architectural divergence. The Jetson Orin Nano Super includes 32 tensor cores, a hallmark of NVIDIA's Ampere generation for AI inference and matrix math. The Ryzen Z2 GPU lists no tensor cores at all, meaning any AI workload must run on the general-purpose shader units. The presence of tensor cores in the NVIDIA part also aligns with its FP16 2:1 ratio, which is typical of Ampere's use of tensor paths for mixed-precision work.

Where Each One Wins

The data points to distinct strengths for each processor based on the recorded specifications. The AMD Ryzen Z2 GPU wins decisively in raw graphics throughput. Its FP32 compute of 8.294 TFLOPS, pixel rate of 86.40 GPixel/s, and texture rate of 129.6 GTexel/s position it as the stronger choice for conventional 3D rendering, where shader complexity and fill rate dominate. The 12 ray tracing cores give it a capability the NVIDIA part entirely lacks, making it the only option of the two for hardware-accelerated ray tracing workloads.

The AMD part also wins on memory capacity and bandwidth. Doubling the RAM from 8 GB to 16 GB allows larger textures, higher resolution assets, and bigger working sets in a single pass. The bandwidth advantage of 119.9 GB/s versus 102.4 GB/s reinforces this lead, particularly for streaming-heavy scenes or large data buffers.

The NVIDIA Jetson Orin Nano Super wins in the domain of AI and tensor-based computation. Its 32 tensor cores provide dedicated hardware for matrix operations, and its FP16 throughput of 4.178 TFLOPS, while lower than AMD's absolute FP16 number, comes from a 2:1 ratio that indicates efficient half-precision paths. The absence of tensor cores in the AMD part means any neural network inference or training task would rely on general-purpose shaders, which lack the specialized datapaths for fused multiply-add matrix operations.

The NVIDIA part also wins on physical footprint and integration flexibility. Its dimensions are recorded as 70 mm by 45 mm, and it carries no power connectors, relying on a 25 W TDP. The AMD part has no dimensions recorded but lists a single USB Type-C display output, while the NVIDIA part's display outputs are described as portable device dependent. The NVIDIA part's PCIe 4.0 x4 interface provides a standard system connection path, whereas the AMD part's bus interface is not recorded.

Specification Differences

The two processors differ across nearly every recorded specification field, with only a few shared attributes. Both support DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4, so API compatibility is identical. Both use a 128-bit memory bus. Both are in active production status. Both have a 50th percentile ranking among all GPUs in the database.

Process node: AMD uses 4 nm at TSMC; NVIDIA uses 8 nm at Samsung. Transistor count: AMD records 25,390 million; NVIDIA records unknown. Die size: AMD at 178 mm² versus NVIDIA at 200 mm². Transistor density: AMD at 142.6M per mm²; no NVIDIA figure.

Clocks: AMD base clock 800 MHz, boost 2700 MHz, memory clock 937 MHz (7.5 Gbps effective). NVIDIA lists no base or boost clock, memory clock 800 MHz (6.4 Gbps effective). Memory capacity: 16 GB LPDDR5X versus 8 GB LPDDR5. Bandwidth: 119.9 GB/s versus 102.4 GB/s.

Compute units: shading units 768 versus 1024; TMUs 48 versus 32; ROPs 32 versus 16; ray tracing cores 12 versus none; tensor cores none versus 32. Pixel rate: 86.40 GPixel/s versus 16.32 GPixel/s. Texture rate: 129.6 GTexel/s versus 32.64 GTexel/s. FP32: 8.294 TFLOPS versus 2.089 TFLOPS. FP16: 8.294 TFLOPS (1:1) versus 4.178 TFLOPS (2:1).

TDP: 28 W versus 25 W. Power connectors: none for AMD; not recorded for NVIDIA. Bus interface: not recorded for AMD; PCIe 4.0 x4 for NVIDIA. Display outputs: 1x USB Type-C for AMD; portable device dependent for NVIDIA. Dimensions: none for AMD; 70 mm by 45 mm for NVIDIA. Release dates: AMD on 2024-12-31, NVIDIA on 2024-12-16. Launch MSRP: none for AMD; 249 USD for NVIDIA.

FAQ

Q: Which processor has higher FP32 compute performance?

A: The AMD Ryzen Z2 GPU delivers 8.294 TFLOPS of FP32, which is approximately 3.97 times the 2.089 TFLOPS of the NVIDIA Jetson Orin Nano Super.

Q: Does the NVIDIA part support ray tracing?

A: No. The database records 12 ray tracing cores for the AMD Ryzen Z2 GPU and none for the NVIDIA Jetson Orin Nano Super.

Q: What is the memory bandwidth difference?

A: The AMD part achieves 119.9 GB/s with LPDDR5X memory, while the NVIDIA part achieves 102.4 GB/s with LPDDR5. Both use a 128-bit bus, but the AMD memory clock of 937 MHz (7.5 Gbps effective) exceeds the NVIDIA 800 MHz (6.4 Gbps effective).

Q: Why does the NVIDIA part have higher FP16 than FP32?

A: The Jetson Orin Nano Super uses a 2:1 FP16 ratio, doubling its FP32 rate of 2.089 TFLOPS to 4.178 TFLOPS in half precision. The AMD part uses a 1:1 ratio, keeping FP16 equal to its FP32 at 8.294 TFLOPS.

Q: What is the transistor density of each chip?

A: The AMD Ryzen Z2 GPU records 142.6 million transistors per square millimeter on a 178 mm² die with 25,390 million transistors. The NVIDIA Jetson Orin Nano Super has an unknown transistor count and no density figure, with a 200 mm² die.

Q: Do both processors support the same graphics APIs?

A: Yes. Both list DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4 as their supported APIs.

The Verdict

The recorded data separates these two processors by their intended workloads rather than by overall superiority. The AMD Ryzen Z2 GPU dominates every measured throughput category: FP32, FP16, pixel fill, texture fill, memory bandwidth, and memory capacity. Its 8.294 TFLOPS FP32, 86.40 GPixel/s pixel rate, and 129.6 GTexel/s texture rate, combined with 12 ray tracing cores and 16 GB of LPDDR5X, make it the clear choice for graphics-intensive applications, real-time rendering, or any workload that demands the highest raw shader output. The 28 W TDP and single USB Type-C output suggest a compact, power-conscious design that still reaches 50th percentile standing among all GPUs.

The NVIDIA Jetson Orin Nano Super targets a different use case. Its 32 tensor cores and 4.178 TFLOPS FP16 throughput indicate a design optimized for AI inference and edge computing, where tensor operations matter more than pixel fill. Its 25 W TDP, 70 mm by 45 mm dimensions, PCIe 4.0 x4 interface, and portable-device-dependent display outputs point toward embedded system integration rather than standalone graphics. The 249 USD launch MSRP provides a reference point, though the AMD part has no recorded launch price.

Users seeking a GPU for traditional 3D graphics, ray tracing, or high-resolution rendering should look to the AMD Ryzen Z2 GPU, as every compute and fill rate metric favors it. Users needing dedicated tensor acceleration for neural network inference in a small, low-power module should consider the NVIDIA Jetson Orin Nano Super, which trades roughly 75 percent of FP32 throughput for specialized AI hardware and a smaller physical footprint. The data shows two valid designs serving different priorities, with the AMD part winning on raw graphics performance and the NVIDIA part winning on tensor-specific capability.