ONNX Runtime v1.23.0

Announcements

• This release introduces Execution Provider (EP) Plugin API, which is a new infrastructure for building plugin-based EPs. (#24887 , #25137, #25124, #25147, #25127, #25159, #25191, #2524)

• This release introduces the ability to dynamically download and install execution providers. This feature is exclusively available in the WinML build and requires Windows 11 version 25H2 or later. To leverage this new capability, C/C++/C# users should use the builds distributed through the Windows App SDK, and Python users should install the onnxruntime-winml package(will be published soon). We encourage users who can upgrade to the latest Windows 11 to utilize the WinML build to take advantage of this enhancement.

Upcoming Changes

• The next release will stop providing x86_64 binaries for macOS and iOS operating systems.
• The next release will increase the minimum supported macOS version from 13.4 to 14.0.
• The next release will stop providing python 3.10 wheels.

Execution & Core Optimizations

Shutdown logic on Windows is simplified

Now on Windows some global object will be not destroyed if we detect that the process is being shutting down(#24891) . It will not cause memory leak as when a process ends all the memory will be returned to the operating system. This change can reduce the chance of having crashes on process exit.

AutoEP/Device Management

Now ONNX Runtime has the ability to automatically discovery computing devices and select the best EPs to download and register. The EP downloading feature currently only works on Windows 11 version 25H2 or later.

Execution Provider (EP) Updates

ROCM EP was removed from the source tree. Users are recommended to use Migraphx or Vitis AI EPs from AMD.
A new EP, Nvidia TensorRT RTX, was added.

Web

EMDSK is upgraded from 4.0.4 to 4.0.8

WebGPU EP

Added WGSL template support.

QNN EP

SDK Update: Added support for QNN SDK 2.37.

KleidiAI

Enhanced performance for SGEMM, IGEMM, and Dynamic Quantized MatMul operations, especially for Conv2D operators on hardware that supports SME2 (Scalable Matrix Extension v2).

Known Problems

• There was a change in build.py that was related to KleidiAI that may cause build failures when doing cross-compiling (#26175) .

Contributions

Contributors to ONNX Runtime include members across teams at Microsoft, along with our community members:

@1duo, @Akupadhye, @amarin16, @AndreyOrb, @ankan-ban, @ankitm3k, @anujj, @aparmp-quic, @arnej27959, @bachelor-dou, @benjamin-hodgson, @Bonoy0328, @chenweng-quic, @chuteng-quic, @clementperon, @co63oc, @daijh, @damdoo01-arm, @danyue333, @fanchenkong1, @gedoensmax, @genarks, @gnedanur, @Honry, @huaychou, @ianfhunter, @ishwar-raut1, @jing-bao, @joeyearsley, @johnpaultaken, @jordanozang, @JulienMaille, @keshavv27, @kevinch-nv, @khoover, @krahenbuhl, @kuanyul-quic, @mauriciocm9, @mc-nv, @minfhong-quic, @mingyueliuh, @MQ-mengqing, @NingW101, @notken12, @omarhass47, @peishenyan, @pkubaj, @qc-tbhardwa, @qti-jkilpatrick, @qti-yuduo, @quic-ankus, @quic-ashigarg, @quic-ashwshan, @quic-calvnguy, @quic-hungjuiw, @quic-tirupath, @qwu16, @ranjitshs, @saurabhkale17, @schuermans-slx, @sfatimar, @stefantalpalaru, @sunnyshu-intel, @TedThemistokleous, @thevishalagarwal, @toothache, @umangb-09, @vatlark, @VishalX, @wcy123, @xhcao, @xuke537, @zhaoxul-qti

ONNX Runtime v1.22.2

What's new?

This release adds an optimized CPU/MLAS implementation of DequantizeLinear (8 bit) and introduces the build option client_package_build, which enables default options that are more appropriate for client/on-device workloads (e.g., disable thread spinning by default).

Build System & Packages

• Add –client_package_build option (#25351) - @jywu-msft
• Remove the python installation steps from win-qnn-arm64-ci-pipeline.yml (#25552) - @snnn

CPU EP

• Add multithreaded/vectorized implementation of DequantizeLinear for int8 and uint8 inputs (SSE2, NEON) (#24818) - @adrianlizarraga

QNN EP

• Add support for the Upsample, Einsum, LSTM, and CumSum operators (#24265, #24616, #24646, #24820) - @quic-zhaoxul, @1duo, @chenweng-quic, @Akupadhye
• Fuse scale into Softmax (#24809) - @qti-yuduo
• Enable DSP queue polling when performance is set to “burst” mode (#25361) - @quic-calvnguy
• Update QNN SDK to version 2.36.1 (#25388) - @qti-jkilpatrick
• Include the license file from QNN SDK in the Microsoft.ML.OnnxRunitme.QNN NuGet package (#25158) - @HectorSVC

ONNX Runtime v1.22.1

What's new?

This release replaces static linking of dxcore.lib with optional runtime loading, lowering the minimum supported version from Windows 10 22H2 (10.0.22621) to 20H1 (10.0.19041). This enables compatibility with Windows Server 2019 (10.0.17763), where dxcore.dll may be absent.

• change dependency from gitlab eigen to github eigen-mirror #24884 - @prathikr
• Weaken dxcore dependency #24845 - @skottmckay
• [DML] Restore compatibility with Windows Sdk 10.0.17134.0 #24950 - @JulienMaille
• Disable VCPKG's binary cache #24889 - @snnn

ONNX Runtime v1.22

Announcements

• This release introduces new API's for Model Editor, Auto EP infrastructure, and AOT Compile
• OnnxRuntime GPU packages require CUDA 12.x , packages built for CUDA 11.x are no longer published.
• The min supported Windows version is now 10.0.19041.

GenAI & Advanced Model Features

• Constrained Decoding: Introduced new capabilities for constrained decoding, offering more control over generative AI model outputs.

Execution & Core Optimizations

Core

• Auto EP Selection Infrastructure: Added foundational infrastructure to enable automatic selection of Execution Providers via selection policies, aiming to simplify configuration and optimize performance. (Pull Request #24430)
• Compile API: Introduced new APIs to support explicit compilation of ONNX models.
  • See: OrtCompileApi Struct Reference (Assuming a similar link structure for future documentation)
  • See: EP Context Design (Assuming a similar link structure for future documentation)
• Model Editor API api's for creating or editing ONNX models
  • See: OrtModelEditorApi

Execution Provider (EP) Updates

CPU EP/MLAS

• KleidiAI Integration: Integrated KleidiAI into ONNX Runtime/MLAS for enhanced performance on Arm architectures.
• MatMulNBits Support: Added support for MatMulNBits, enabling matrix multiplication with weights quantized to 8 bits.
• GroupQueryAttention optimizations and enhancements

OpenVINO EP

• Added support up to OpenVINO 2025.1
• Introduced Intel compiler level optimizations for QDQ models.
• Added support to select Intel devices based on LUID
• Load_config feature improvement to support AUTO, HETERO and MULTI plugin.
• misc bugfixes/optimizations
• For detailed updates, refer to Pull Request #24394: ONNXRuntime OpenVINO - Release 1.22

QNN EP

• SDK Update: Added support for QNN SDK 2.33.2.
• operator updates/support to Sum, Softmax, Upsample, Expand, ScatterND, Einsum
• QNN EP can be built as shared or static library.
• enable QnnGpu backend
• For detailed updates refer to recent QNN tagged PR's

TensorRT EP

• TensorRT Version: Added support for TensorRT 10.9.
  • Note for onnx-tensorrt open-source parser users: Please check here for specific requirements (Referencing 1.21 link as a placeholder, this should be updated for 1.22).
• New Features:
  • EP option to enable TRT Preview Feature
  • Support to load TensorRT V3 plugin
• Bug Fixes:
  • Resolved an issue related to multithreading scenarios.
  • Fixed incorrect GPU usage that affected both TensorRT EP and CUDA EP.

NV TensorRT RTX EP

• New Execution Provider: Introduced a new Execution Provider specifically for Nvidia RTX GPUs, leveraging TensorRT for optimized performance.

CUDA EP

• MatMulNBits Enhancement: Added support for 8-bit weight-only quantization in MatMulNBits.
• Bug Fixes:
  • Fixed incorrect GPU usage (also mentioned under TensorRT EP).

VitisAI EP

• Miscellaneous bug fixes and improvements.

Infrastructure & Build Improvements

Build System & Packages

• QNN Nuget Package: The QNN Nuget package is now built as ARM64x.

Dependencies / Version Updates

• CUDA Version Update: This release includes an update to the CUDA version. Users should consult the documentation for specific version requirements. CUDA 11 based GPU packages no longer published.

Web

• WebGPU Expansion:
  • Added WebGPU support to the node.js package (Windows and macOS).
  • Enabled WebGPU when building from source for macOS, Linux, and Windows.

Mobile

• No major updates of note this release.

Contributions

Contributors to ONNX Runtime include members across teams at Microsoft, along with our community members:

Yulong Wang, Jian Chen, Changming Sun, Satya Kumar Jandhyala, Hector Li, Prathik Rao, Adrian Lizarraga, Jiajia Qin, Scott McKay, Jie Chen, Tianlei Wu, Edward Chen, Wanming Lin, xhcao, vraspar, Dmitri Smirnov, Jing Fang, Yifan Li, Caroline Zhu, Jianhui Dai, Chi Lo, Guenther Schmuelling, Ryan Hill, Sushanth Rajasankar, Yi-Hong Lyu, Ankit Maheshkar, Artur Wojcik, Baiju Meswani, David Fan, Enrico Galli, Hans, Jambay Kinley, John Paul, Peishen Yan, Yateng Hong, amarin16, chuteng-quic, kunal-vaishnavi, quic-hungjuiw, Alessio Soldano, Andreas Hussing, Ashish Garg, Ashwath Shankarnarayan, Chengdong Liang, Clément Péron, Erick Muñoz, Fanchen Kong, George Wu, Haik Silm, Jagadish Krishnamoorthy, Justin Chu, Karim Vadsariya, Kevin Chen, Mark Schofield, Masaya, Kato, Michael Tyler, Nenad Banfic, Ningxin Hu, Praveen G, Preetha Veeramalai, Ranjit Ranjan, Seungtaek Kim, Ti-Tai Wang, Xiaofei Han, Yueqing Zhang, co63oc, derdeljan-msft, genmingz@AMD, jiangzhaoming, jing-bao, kuanyul-quic, liqun Fu, minfhong-quic, mingyue, quic-tirupath, quic-zhaoxul, saurabh, selenayang888, sfatimar, sheetalarkadam, virajwad, zz002, Ștefan Talpalaru

ONNX Runtime v1.21.1

What's new?

• Extend CMAKE_CUDA_FLAGS with all Blackwell compute capacity #23928 - @yf711
• [ARM CPU] Fix fp16 const initialization on no-fp16 platform #23978 - @fajin-corp
• [TensorRT EP] Call cudaSetDevice at compute function for handling multithreading scenario #24010 - @chilo-ms
• Fix attention bias broadcast #24017 - @tianleiwu
• Deleted the constant SKIP_CUDA_TEST_WITH_DML #24113 - @CodingSeaotter
• [QNN EP] ARM64EC python package remove --vcpkg in build #24174 - @jywu-msft
• [wasm] remove --vcpkg in wasm build #24179 - @fs-eire

ONNX Runtime v1.21.0

Announcements

• No large announcements of note this release! We've made a lot of small refinements to streamline your ONNX Runtime experience.

GenAI & Advanced Model Features

Enhanced Decoding & Pipeline Support

• Added "chat mode" support for CPU, GPU, and WebGPU.
• Provided support for decoder model pipelines.
• Added support for Java API for MultiLoRA.

API & Compatibility Updates

• Chat mode introduced breaking changes in the API (see migration guide).

Bug Fixes for Model Output

• Fixed Phi series garbage output issues with long prompts.
• Resolved gibberish issues with top_k on CPU.

Execution & Core Optimizations

Core Refinements

• Reduced default logger usage for improved efficiency(#23030).
• Fixed a visibility issue in theadpool (#23098).

Execution Provider (EP) Updates

General

• Removed TVM EP from the source tree(#22827).
• Marked NNAPI EP for deprecation (following Google's deprecation of NNAPI).
• Fixed a DLL delay loading issue that impacts WebGPU EP and DirectML EP's usability on Windows (#23111, #23227)

TensorRT EP Improvements

• Added support for TensorRT 10.8.
  • onnx-tensorrt open-source parser user: please check here for requirement.
• Assigned DDS ops (NMS, RoiAlign, NonZero) to TensorRT by default.
• Introduced option trt_op_types_to_exclude to exclude specific ops from TensorRT assignment.

CUDA EP Improvements

• Added a python API preload_dlls to coexist with PyTorch.
• Miscellaneous enhancements for Flux model inference.

QNN EP Improvements

• Introduced QNN shared memory support.
• Improved performance for AI Hub models.
• Added support for QAIRT/QNN SDK 2.31.
• Added Python 3.13 package.
• Miscellaneous bug fixes and enhancements.
• QNN EP is now built as a shared library/DLL by default. To retain previous build behavior, use build option --use_qnn static_lib.

DirectML EP Support & Upgrades

• Updated DirectML version from 1.15.2 to 1.15.4(#22635).

OpenVINO EP Improvements

• Introduced OpenVINO EP Weights Sharing feature.
• Added support for various contrib Ops in OVEP:
  • SkipLayerNormalization, MatMulNBits, FusedGemm, FusedConv, EmbedLayerNormalization, BiasGelu, Attention, DynamicQuantizeMatMul, FusedMatMul, QuickGelu, SkipSimplifiedLayerNormalization
• Miscellaneous bug fixes and improvements.

VitisAI EP Improvements

• Miscellaneous bug fixes and improvements.

Mobile Platform Enhancements

CoreML Updates

• Added support for caching generated CoreML models.

Extensions & Tokenizer Improvements

Expanded Tokenizer Support

• Now supports more tokenizer models, including ChatGLM, Baichuan2, Phi-4, etc.
• Added full Phi-4 pre/post-processing support for text, vision, and audio.
• Introduced RegEx pattern loading from tokenizer.json.

Image Codec Enhancements

• ImageCodec now links to native APIs if available; otherwise, falls back to built-in libraries.

Unified Tokenizer API

• Introduced a new tokenizer op schema to unify the tokenizer codebase.
• Added support for loading tokenizer data from a memory blob in the C API.

Infrastructure & Build Improvements

Runtime Requirements

All the prebuilt Windows packages now require VC++ Runtime version >= 14.40(instead of 14.38). If your VC++ runtime version is lower than that, you may see a crash when ONNX Runtime was initializing. See https://github.com/microsoft/STL/wiki/Changelog#vs-2022-1710 for more details.

Updated minimum iOS and Android SDK requirements to align with React Native 0.76:

• iOS >= 15.1
• Android API >= 24 (Android 7)

All macOS packages now require macOS version >= 13.3.

CMake File Changes

CMake Version: Increased the minimum required CMake version from 3.26 to 3.28. Added support for CMake 4.0.
Python Version: Increased the minimum required Python version from 3.8 to 3.10 for building ONNX Runtime from source.
Improved VCPKG support

Added the following cmake options for WebGPU EP

• onnxruntime_USE_EXTERNAL_DAWN
• onnxruntime_CUSTOM_DAWN_SRC_PATH
• onnxruntime_BUILD_DAWN_MONOLITHIC_LIBRARY
• onnxruntime_ENABLE_PIX_FOR_WEBGPU_EP
• onnxruntime_ENABLE_DAWN_BACKEND_VULKAN
• onnxruntime_ENABLE_DAWN_BACKEND_D3D12

Added cmake option onnxruntime_BUILD_QNN_EP_STATIC_LIB for building with QNN EP as a static library.
Removed cmake option onnxruntime_USE_PREINSTALLED_EIGEN.

Fixed a build issue with Visual Studio 2022 17.3 (#23911)

Modernized Build Tools

• Now using VCPKG for most package builds.
• Upgraded Gradle from 7.x to 8.x.
• Updated JDK from 11 to 17.
• Enabled onnxruntime_USE_CUDA_NHWC_OPS by default for CUDA builds.
• Added support for WASM64 (build from source; no package published).

Dependency Cleanup

• Removed Google’s nsync from dependencies.

Others

Updated Node.js installation script to support network proxy usage (#23231)

Web

• No updates of note.

Contributors

Contributors to ONNX Runtime include members across teams at Microsoft, along with our community members:

Changming Sun, Yulong Wang, Tianlei Wu, Jian Chen, Wanming Lin, Adrian Lizarraga, Hector Li, Jiajia Qin, Yifan Li, Edward Chen, Prathik Rao, Jing Fang, shiyi, Vincent Wang, Yi Zhang, Dmitri Smirnov, Satya Kumar Jandhyala, Caroline Zhu, Chi Lo, Justin Chu, Scott McKay, Enrico Galli, Kyle, Ted Themistokleous, dtang317, wejoncy, Bin Miao, Jambay Kinley, Sushanth Rajasankar, Yueqing Zhang, amancini-N, ivberg, kunal-vaishnavi, liqun Fu, Corentin Maravat, Peishen Yan, Preetha Veeramalai, Ranjit Ranjan, Xavier Dupré, amarin16, jzm-intel, kailums, xhcao, A-Satti, Aleksei Nikiforov, Ankit Maheshkar, Javier Martinez, Jianhui Dai, Jie Chen, Jon Campbell, Karim Vadsariya, Michael Tyler, PARK DongHa, Patrice Vignola, Pranav Sharma, Sam Webster, Sophie Schoenmeyer, Ti-Tai Wang, Xu Xing, Yi-Hong Lyu, genmingz@AMD, junchao-zhao, sheetalarkadam, sushraja-msft, Akshay Sonawane, Alexis Tsogias, Ashrit Shetty, Bilyana Indzheva, Chen Feiyue, Christian Larson, David Fan, David Hotham, Dmitry Deshevoy, Frank Dong, Gavin Kinsey, George Wu, Grégoire, Guenther Schmuelling, Indy Zhu, Jean-Michaël Celerier, Jeff Daily, Joshua Lochner, Kee, Malik Shahzad Muzaffar, Matthieu Darbois, Michael Cho, Michael Sharp, Misha Chornyi, Po-Wei (Vincent), Sevag H, Takeshi Watanabe, Wu, Junze, Xiang Zhang, Xiaoyu, Xinpeng Dou, Xinya Zhang, Yang Gu, Yateng Hong, mindest, mingyue, raoanag, saurabh, shaoboyan091, sstamenk, tianf-fff, wonchung-microsoft, xieofxie, zz002

ONNX Runtime v1.20.2 [QNN-only]

What's new?

Build System & Packages

• Merge Windows machine pools for Web CI pipeline to reduce maintenance costs (#23243) - @snnn
• Update boost URL for React Native CI pipeline (#23281) - @jchen351
• Move ORT Training pipeline to GitHub actions and enable CodeQL scan for the source code (#22543) - @snnn
• Move Linux GitHub actions to a dedicated machine pool (#22566) - @snnn
• Update Apple deployment target to iOS 15.1 and macOS 13.3 (#23308) - @snnn
• Deprecate macOS 12 in packaging pipeline (#23017) - @mszhanyi
• Remove net8.0-android MAUI target from MAUI test project (#23607) - @carzh

CUDA EP

• Fixes use of numeric_limits that causes a compiler error in Visual Studio 2022 v17.12 Preview 5 (#22738, #22868) - @tianleiwu

QNN EP

• Enable offloading graph input quantization and graph output dequantization to CPU by default. Improves inference latency by reducing the amount of I/O data copied between CPU and NPU. (#23368) - @adrianlizarraga

ONNX Runtime v1.20.1

What's new?

Python Quantization Tool

• Prevent int32 quantized bias from clipping by adjusting the weight's scale (#22020) - @adrianlizarraga
• Update QDQ Pad, Slice, Softmax (#22676) - @adrianlizarraga
• Introduce get_qdq_config() helper to get QDQ configurations (#22677) - @adrianlizarraga
• Add reduce_range option to get_qdq_config() (#22782) - @adrianlizarraga
• Flaky test due to Pad reflect bug (#22798) - @adrianlizarraga

CPU EP

• Refactor SkipLayerNorm implementation to address issues (#22719, #22862) - @amarin16, @liqunfu

QNN EP

• Add QNN SDK v2.28.2 support (#22724, #22844) - @HectorSVC, @adrianlizarraga

TensorRT EP

• Exclude DDS ops from running on TRT (#22875) - @chilo-ms

Packaging

• Rework the native library usage so that a pre-built ORT native package can be easily used (#22345) - @skottmckay
• Fix Maven Sha256 Checksum Issue (#22600) - @idiskyle

Contributions

Big thank you to the release manager @yf711, along with @adrianlizarraga, @HectorSVC, @jywu-msft, and everyone else who helped to make this patch release process a smooth one!

ONNX Runtime v1.20.0

Release Manager: @apsonawane

Announcements

• All ONNX Runtime Training packages have been deprecated. ORT 1.19.2 was the last release for which onnxruntime-training (PyPI), onnxruntime-training-cpu (PyPI), Microsoft.ML.OnnxRuntime.Training (Nuget), onnxruntime-training-c (CocoaPods), onnxruntime-training-objc (CocoaPods), and onnxruntime-training-android (Maven Central) were published.
• ONNX Runtime packages will stop supporting Python 3.8 and Python 3.9. This decision aligns with NumPy Python version support. To continue using ORT with Python 3.8 and Python 3.9, you can use ORT 1.19.2 and earlier.
• ONNX Runtime 1.20 CUDA packages will include new dependencies that were not required in 1.19 packages. The following dependencies are new: libcudnn_adv.so.9, libcudnn_cnn.so.9, libcudnn_engines_precompiled.so.9, libcudnn_engines_runtime_compiled.so.9, libcudnn_graph.so.9, libcudnn_heuristic.so.9, libcudnn_ops.so.9, libnvrtc.so.12, and libz.so.1.

Build System & Packages

• Python 3.13 support is included in PyPI packages.
• ONNX 1.17 support will be delayed until a future release, but the ONNX version used by ONNX Runtime has been patched to include a shape inference change to the Einsum op.
• DLLs in the Maven build are now digitally signed (fix for issue reported here).
• (Experimental) vcpkg support added for the CPU EP. The DML EP does not yet support vcpkg, and other EPs have not been tested.

Core

• MultiLoRA support.
• Reduced memory utilization.
  • Fixed alignment that was causing mmap to fail for external weights.
  • Eliminated double allocations when deserializing external weights.
  • Added ability to serialize pre-packed weights so that they don’t cause an increase in memory utilization when the model is loaded.
• Support bfloat16 and float8 data types in python I/O binding API.

Performance

• INT4 quantized embedding support on CPU and CUDA EPs.
• Miscellaneous performance improvements and bug fixes.

EPs

CPU

• FP16 support for MatMulNbits, Clip, and LayerNormalization ops.

CUDA

• Cudnn frontend integration for convolution operators.
• Added support of cuDNN Flash Attention and Lean Attention in MultiHeadAttention op.

TensorRT

• TensorRT 10.4 and 10.5 support.

QNN

• QNN HTP support for weight sharing across multiple ORT inference sessions. (See ORT QNN EP documentation for more information.)
• Support for QNN SDK 2.27.

OpenVINO

• Added support up to OpenVINO 2024.4.1.
• Compile-time memory optimizations.
• Enhancement of ORT EPContext Session option for optimized first inference latency.
• Added remote tensors to ensure direct memory access for inferencing on NPU.

DirectML

• DirectML 1.15.2 support.

Mobile

• Improved Android QNN support, including a pre-built Maven package and various performance improvements.
• FP16 support for ML Program models with CoreML EP.
• FP16 XNNPACK kernels to provide a fallback option if CoreML is not available at runtime.
• Initial support for using the native WebGPU EP on Android and iOS. _Note: The set of initial operators is limited, and the code is available from the main branch, not ORT 1.20 packages. See #22591 for more information.

Web

• Quantized embedding support.
• On-demand weight loading support (offloads Wasm32 heap and enables 8B-parameter LLMs).
• Integrated Intel GPU performance improvements.
• Opset-21 support (Reshape, Shape, Gelu).

GenAI

• MultiLoRA support.
• Generations can now be terminated mid-loop.
• Logit soft capping support in Group Query Attention (GQA).
• Additional model support, including Phi-3.5 Vision Multi-Frame, ChatGLM3, and Nemotron-Mini.
• Python package now available for Mac.
• Mac / iOS now available in NuGet packages.

Full release notes for ONNX Runtime generate() API v0.5.0 can be found here.

Extensions

• Tokenization performance improvements.
• Support for latest Hugging Face tokenization JSON format (transformers>=4.45).
• Unigram tokenization model support.
• OpenCV dependency removed from C API build.

Full release notes for ONNX Runtime Extensions v0.13 can be found here.

Olive

• Olive command line interface (CLI) now available with support to execute well-defined, concrete workflows without the need to create or edit configs manually.
• Additional improvements, including support for YAML-based workflow configs, streamlined DataConfig management, simplified workflow configuration, and more.
• Llama and Phi-3 model updates, including an updated MultiLoRA example using the ORT generate() API.
  Full release notes for Olive v0.7.0 can be found here.

Contributors

Big thank you to the release manager @apsonawane, as well as @snnn, @jchen351, @sheetalarkadam, and everyone else who made this release possible!

Tianlei Wu, Yi Zhang, Yulong Wang, Scott McKay, Edward Chen, Adrian Lizarraga, Wanming Lin, Changming Sun, Dmitri Smirnov, Jian Chen, Jiajia Qin, Jing Fang, George Wu, Caroline Zhu, Hector Li, Ted Themistokleous, mindest, Yang Gu, jingyanwangms, liqun Fu, Adam Pocock, Patrice Vignola, Yueqing Zhang, Prathik Rao, Satya Kumar Jandhyala, Sumit Agarwal, Xu Xing, aciddelgado, duanshengliu, Guenther Schmuelling, Kyle, Ranjit Ranjan, Sheil Kumar, Ye Wang, kunal-vaishnavi, mingyueliuh, xhcao, zz002, 0xdr3dd, Adam Reeve, Arne H Juul, Atanas Dimitrov, Chen Feiyue, Chester Liu, Chi Lo, Erick Muñoz, Frank Dong, Jake Mathern, Julius Tischbein, Justin Chu, Xavier Dupré, Yifan Li, amarin16, anujj, chenduan-amd, saurabh, sfatimar, sheetalarkadam, wejoncy, Akshay Sonawane, AlbertGuan9527, Bin Miao, Christian Bourjau, Claude, Clément Péron, Emmanuel, Enrico Galli, Fangjun Kuang, Hann Wang, Indy Zhu, Jagadish Krishnamoorthy, Javier Martinez, Jeff Daily, Justin Beavers, Kevin Chen, Krishna Bindumadhavan, Lennart Hannink, Luis E. P., Mauricio A Rovira Galvez, Michael Tyler, PARK DongHa, Peishen Yan, PeixuanZuo, Po-Wei (Vincent), Pranav Sharma, Preetha Veeramalai, Sophie Schoenmeyer, Vishnudas Thaniel S, Xiang Zhang, Yi-Hong Lyu, Yufeng Li, goldsteinn, mcollinswisc, mguynn-intc, mingmingtasd, raoanag, shiyi, stsokolo, vraspar, wangshuai09

Full changelog: v1.19.2...v1.20.0

ONNX Runtime v1.19.2

Announcements

• ORT 1.19.2 is a small patch release, fixing some broken workflows and introducing bug fixes.

Build System & Packages

• Fixed the signing of native DLLs.
• Disabled absl symbolize in Windows Release build to avoid dependency on dbghelp.dll.

Training

• Restored support for CUDA compute capability 7.0 and 7.5 with CUDA 12, and 6.0 and 6.1 with CUDA 11.
• Several fixes for training CI pipelines.

Mobile

• Fixed ArgMaxOpBuilder::AddToModelBuilderImpl() nullptr Node access for CoreML EP.

Generative AI

• Added CUDA kernel for Phi3 MoE.
• Added smooth softmax support in CUDA and CPU kernels for the GroupQueryAttention operator.
• Fixed number of splits calculations in GroupQueryAttention CUDA operator.
• Enabled causal support in the MultiHeadAttention CUDA operator.

Contributors

@prathikr, @mszhanyi, @edgchen1, @tianleiwu, @wangyems, @aciddelgado, @mindest, @snnn, @baijumeswani, @MaanavD

Thanks to everyone who helped ship this release smoothly!

Full Changelog: v1.19.0...v1.19.2