We're excited to announce we're expanding our AI Inference benchmark offerings with the UL Procyon AI Image Generation Benchmark, coming Monday, 25th March. AI has the potential to be one of the most significant new technologies hitting the mainstream this decade, and many industry leaders are competing to deliver the best AI Inference performance through their hardware. Last year, we launched the first of our Procyon AI Inference Benchmarks for Windows, which measured AI Inference performance with a workload using Computer Vision.

The upcoming UL Procyon AI Image Generation Benchmark provides a consistent, accurate and understandable workload for measuring the AI performance of high-end hardware, built with input from members of the industry to ensure fair and comparable results across all supported hardware.

Qualcomm Snapdragon X Elite is about to make landfall in the ultraportable notebook segment, powering a new wave of Windows 11 devices powered by Arm, capable of running even legacy Windows applications. The Snapdragon X Elite SoC in particular has been designed to rival the Apple M3 chip powering the 2024 MacBook Air, and some of the "entry-level" variants of the 2023 MacBook Pros. These chips threaten the 15 W U-segment and even 28 W P-segment of x86-64 processors from Intel, such as the Core Ultra "Meteor Lake," and Ryzen 8040 "Hawk Point." Erdi Özüağ, prominent tech journalist from Türkiye, has access to a Qualcomm-reference notebook powered by the Snapdragon X Elite X1E80100 28 W SoC. He compared its performance to an off-the-shelf notebook powered by a 28 W Intel Core Ultra 7 155H "Meteor Lake" processor.

There are three tests that highlight the performance of the key components of the SoCs—CPU, iGPU, and NPU. A Microsoft Visual Studio code compile test sees the Snapdragon X Elite with its 12-core Oryon CPU finish the test in 37 seconds; compared to 54 seconds by the Core Ultra 7 155H with its 6P+8E+2LP CPU. In the 3DMark test, the Adreno 750 iGPU posts identical performance numbers to the Arc Graphics Xe-LPG of the 155H. Where the Snapdragon X Elite dominates the Intel chip is AI inferencing. The UL Procyon test sees the 45 TOPS NPU of the Snapdragon X Elite score 1720 points compared to 476 points by the 10 TOPS AI Boost NPU of the Core Ultra. The Intel machine is using OpenVINO, while the Snapdragon is using Qualcomm SNPE SDK for the test. Don't forget to check out the video review by Erdi Özüağ in the source link below.

We already know about AMD Ryzen 7 8700G APU's enjoyment of overclocked memory—early reviews demonstrated the graphical benefits granted by fiddling with "iGPU engine clock and the processor's memory frequency." While gamers can enjoy a boosted integrated graphics solution that is comparable in performance 1080p stakes to a discrete Radeon RX 6500 XT GPU, AI enthusiasts are eager to experiment with the "Hawk Point" pat's Radeon 780M IGP and Neural Processing Unit (NPU)—the first generation Ryzen XDNA inference engine can unleash up to 16 AI TOPs. One individual, chi11eddog, posted their findings through social media channels earlier today, coinciding with the official launch of Ryzen 8000G processors. The initial set of results concentrated on the Radeon 780M aspect; NPU-centric data may arrive at a later date.

They performed quick tests on AMD's freshly released Ryzen 7 8700G desktop processor, combined with an MSI B650 Gaming Plus WiFi motherboard and two sticks of 16 GB DDR5-4800 memory. The MSI exclusive "Memory Try It" feature was deployed further up in the tables—this assisted in achieving and gauging several "higher system RAM frequency" settings. Here is chi11eddog's succinct interpretation of benchmark results: "7600 MT/s is 15% faster than 4800 MT/s in UL Procyon AI Inference Benchmark and 4% faster in GIMP with Stable Diffusion." The processor's default memory state is capable of producing 210 Float32 TOPs, according to chi11eddog's inference chart. The 6000 MT/s setting produces a 7% improvement over baseline, while 7200 MT/s drives proceedings to 11%—the flagship APU's Radeon 780M iGPU appears to be quite dependent on bandwidth. Their GIMP w/ Stable Diffusion benchmarks also taxed the integrated RDNA 3 graphics solution—again, it was deemed to be fairly bandwidth hungry.