A benchmark version number is specific to a test. Benchmark version numbers change rarely and only when absolutely necessary to accommodate changes in third-party applications or bug fixes.

Procyon AI Computer Vision 2.0 Benchmark v1.0.567

May 27, 2026

Updated

  • Added support for local generation of EP Context models for AMD Vitis AI EP. This enables the workload to automatically generate compatible models that benefit from the latest VitisAI EP updates without the need to update the benchmark with every EP release. 
  • Enabled shared memory buffer usage for OpenVINO and QNN Execution Providers. Helps avoid implicit IO memory transfers by utilizing shared memory buffers bringing minor performance improvements 
  • Updated native Intel OpenVINO inference engine to v2026.1 
  • Updated ESRGAN model used in WinML + QNN Execution Provider (EP) path 

Procyon AI Computer Vision 2.0 Benchmark v1.0.557

April 17, 2026

Added

  • Added native Ryzen AI path for systems with AMD NPUs based on XDNA 2 or later architectures.

Procyon AI Computer Vision 2.0 Benchmark v1.0.555

April 13, 2026

Fixed

  • Resolved an issue where an incorrect SNPE DLL was packaged with the WinML QNN Execution Provider runtime.
  • Model cache generated for WinML QNN Execution provider use SDK 2.39 to avoid regression in BLIP model caused by SDK 2.40 driver dependencies. 

Added

  • Model caches generated for the WinML OpenVINO Execution Provider now include the execution provider version in the cache name so that caches can be regenerated when a new OpenVINO EP is released. 
  • Improved error logging for WinML workloads when Execution Providers fail to download.  

Procyon AI Computer Vision 2.0 Benchmark v1.0.539

March 30, 2026

This update is the release version of the AI Computer Vision 2 for Windows.

Release Workloads:

  • Image classification with ConvNeXt
  • Image captioning with BLIP
  • Object detection with DETR
  • Image segmentation with SAM2
  • Video upscaling with Real-ERSGAN

Release Execution and Runtime Support

Windows

  • Support for Microsoft Windows ML as a standardized execution path, with the following execution providers
    • DmlExecutionProvider
    • NvTensorRTRTXExecutionProvider
    • OpenVINOExecutionProvider
    • QNNExecutionProvider
    • VitisAIExecutionProvider
  • Native inference paths remain available for comparison
    • NVIDIA TensorRT
    • Intel OpenVINO
    • Qualcomm SNPE
  • Supported accelerators include GPUs and NPUs across major vendors

macOS

  • Core ML is the default execution path on Apple Silicon-based Macs.