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Release v1.6.0

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@dwithchenna dwithchenna released this 08 Oct 21:59
· 76 commits to main since this release
v1.6.0
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Release Note: Version 1.6.0

  • BF16 Compiler (CNN, Transformer, ASR)

    • BF16 CNN perf improvements average 80% across release

    • BF16 perf improvements - 1.3X faster on CNN than iGPU and 2.6X faster for transformers than iGPU

    • Improved coverage and improved performance for ASR models

    • Average 3x compile time improvement

    • Smaller installation size

    • Reduction in CPU overhead by pushing data layout transformation to NPU

    • Dynamic batch size support for compilation

  • New Integer Compiler (CNN)

    • Support for General Asymmetric Quantization enabling third party quantized models to run on NPU
    • Support for XINT8, A8W8, A16W8

  • LLM

    • Broad Set of NPU only models optimized performance
    • New set of hybrid models with bfp16 activation
    • New architecture support in hybrid flow (Phi-4, Qwen-3)
    • Context length improvement from 2K to 4K for all models.

  • Stable Diffusion Demo

    • 8x Dynamic Resolution for SD3.0/3.5 (text2image and image2imageControlNet)
    • Performance boost for SD 1.5/2.1-base/turbo/XL-turbo
      Support Batch Size 1 for SD-turbo/SDXL-turbo
      New model support (SD2.1-v 768x768 text2image, SDXL-base 1024x1024 text2image)

  • Breaking Changes

    • For running INT8 models on STX/KRK or newer devices, the xclbin provider option is no longer supported and should no longer be used. See Using INT8 Models for full details.

    • For running INT8 models on PHX/HPT devices, the target option should be set to X1. The NPU binary should still be specified using the xclbin provider option. See Using INT8 Models for full details.

    • For BF16 models, the default configurations file requires a new target section. See Config File Options for full details.

    • LLM:

      • OGA version has been updated to v0.9.2 (Ryzen AI 1.6) from v0.7.0 (Ryzen AI 1.5). Any APIs that are obsolete must be updated to the supported equivalents as described in the Microsoft ONNX Runtime GenAI v0.9.2 documentation
      • Hybrid models published with earlier releases are not compatible with Ryzen AI 1.6. Please use the hybrid models published with the 1.6 release.
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