Bump Microsoft.ML.OnnxRuntime from 1.20.1 to 1.24.4

[dependabot]

Updated Microsoft.ML.OnnxRuntime from 1.20.1 to 1.24.4.

Release notes

Sourced from Microsoft.ML.OnnxRuntime's releases.

1.24.4

This is a patch release for ONNX Runtime 1.24, containing bug fixes and execution provider updates.

Bug Fixes

• Core: Added PCI bus fallback for Linux GPU device discovery in containerized environments (e.g., AKS/Kubernetes) where nvidia-drm is not loaded but GPU PCI devices are still exposed via sysfs. (#​27591)
• Plugin EP: Fixed null pointer dereference when iterating output spans in GetOutputIndex. (#​27644)
• Plugin EP: Fixed bug that incorrectly assigned duplicate MetaDef IDs to fused nodes in different GraphViews (e.g., then/else branches of an If node), causing session creation to fail with a conflicting kernel error. (#​27666)

Execution Provider Updates

• QNN EP: Enabled offline x64 compilation with memhandle IO type by deferring rpcmem library loading to inference time. (#​27479)
• QNN EP: Reverted QNN SDK logging verbosity changes that caused segmentation faults on backend destruction. (#​27650)

Build and Infrastructure

• Python: Updated python_requires from >=3.10 to >=3.11 to reflect dropped Python 3.10 support. (#​27354)
• Build: Replaced __builtin_ia32_tpause with the compiler-portable _tpause intrinsic to fix cross-compiler portability issues between GCC and LLVM. (#​27607)

Full Changelog: v1.24.3...v1.24.4

Contributors

@​derdeljan-msft, @​adrianlizarraga, @​apwojcik, @​baijumeswani, @​edgchen1, @​mocknen, @​tianleiwu, @​XXXXRT666

1.24.3

This is a patch release for ONNX Runtime 1.24, containing bug fixes, security improvements, performance enhancements, and execution provider updates.

Security Fixes

• Core: Fixed GatherCopyData integer truncation leading to heap out-of-bounds read/write. (#​27444)
• Core: Fixed RoiAlign heap out-of-bounds read via unchecked batch_indices. (#​27543)
• Core: Prevent heap OOB from maliciously crafted Lora Adapters. (#​27518)
• Core: Fixed out-of-bounds access for Resize operation. (#​27419)

Bug Fixes

• Core: Fixed GatherND division by zero when batch dimensions mismatch. (#​27090)
• Core: Fixed validation for external data paths for models loaded from bytes. (#​27430)
• Core: Fixed SkipLayerNorm fusion incorrectly applied when gamma/beta are not 1D. (#​27459)
• Core: Fixed double-free in TRT EP custom op domain Release functions. (#​27471)
• Core: Fixed QMoE CPU Operator. (#​27360)
• Core: Fixed MatmulNBits prepacking scales. (#​27412)
• Python: Fixed refcount bug in map input conversion that caused shutdown segfault. (#​27413)
• NuGet: Fixed DllImportResolver. (#​27397)
• NuGet: Added OrtEnv.DisableDllImportResolver to prevent fatal error on resolver conflict. (#​27535)

Performance Improvements

• Core: QMoE CPU performance update (up to 4x on 4-bit). (#​27364)
• Core: Fixed O(n²) model load time for TreeEnsemble with categorical feature chains. (#​27391)

Execution Provider Updates

• NvTensorRtRtx EP:
  • Avoid repetitive creation of fp4/fp8 native-custom-op domains. (#​27192)
  • Added missing override specifiers to suppress warnings. (#​27288)
  • DQ→MatMulNBits fusion transformer. (#​27466)
• WebGPU:
  • Used embedded WASM module in Blob URL workers when wasmBinary is provided. (#​27318)
  • Fixed usage of wasmBinary together with a blob URL for .mjs. (#​27411)
  • Removed the unhelpful "Unknown CPU vendor" warning. (#​27399)
  • Allows new memory info name for WebGPU. (#​27475)
• MLAS:
  • Added DynamicQGemm function pointers and ukernel interface. (#​27403)
  • Fixed error where bytes is not assigned for dynamic qgemm pack b size. (#​27421)
• VitisAI EP: Removed s_kernel_registry_vitisaiep.reset() in deinitialize_vitisai_ep(). (#​27295)
• Plugin EPs: Added "library_path" metadata entry to OrtEpDevice instances for plugin and provider bridge EPs. (#​27522)

Build and Infrastructure

• Pipelines:
  • Build Windows ARM64X binaries as part of packaging pipeline. (#​27316)
  • Moved JAR testing pipelines to canonical pipeline template. (#​27480)
• Python: Enabled Python 3.14 CI and upgraded dependencies. (#​27401)
• Build: Suppressed spurious Array Out of Bounds warnings produced by GCC 14.2 compiler on Linux builds. (#​27454)
• Build: Fixed -Warray-bounds build error in MLAS on clang 17+. (#​27499)
• Telemetry: Added/Updated telemetry events. (#​27356)
• Config: Increased kMaxValueLength to 8192. (#​27521)

... (truncated)

1.24.2

This is a patch release for ONNX Runtime 1.24, containing several bug fixes, security improvements, and execution provider updates.

Bug Fixes

• NuGet: Fixed native library loading issues in the ONNX Runtime NuGet package on Linux and macOS. (#​27266)
• macOS: Fixed Java support and Jar testing on macOS ARM64. (#​27271)
• Core: Enable Robust Symlink Support for External Data for Huggingface Hub Cache. (#​27374)
• Core: Added boundary checks for SparseTensorProtoToDenseTensorProto to improve robustness. (#​27323)
• Security: Fixed an out-of-bounds read vulnerability in ArrayFeatureExtractor. (#​27275)

Execution Provider Updates

• MLAS: Fixed flakiness and accuracy issues in Lut GEMM (MatMulNBitsLutGemm). (#​27216)
• QNN: Enabled 64-bit UDMA mode for HTP target v81 or above. (#​26677)
• WebGPU:
  • Used LazyRelease for prepack allocator. (#​27077)
  • Fixed ConvTranspose bias validation in both TypeScript and C++ implementations. (#​27213)
• OpenVINO (OVEP): Patch to reduce resident memory by reusing weight files across shared contexts. (#​27238)
• DNNL: Fixed DNNL build error by including missing files. (#​27334)

Build and Infrastructure

• CUDA:
  • Added support for CUDA architecture family codes (suffix 'f') introduced in CUDA 12.9. (#​27278)
  • Fixed build errors and warnings for various CUDA versions (12.8, 13.0, 13.1.1). (#​27276)
  • Applied patches for Abseil CUDA warnings. (#​27096, #​27126)
• Pipelines:
  • Fixed Python packaging pipeline for Windows ARM64 and release. (#​27339, #​27350, #​27299)
  • Fixed DirectML NuGet pipeline to correctly bundle x64 and ARM64 binaries for release. (#​27349)
  • Updated Microsoft.ML.OnnxRuntime.Foundry package for Windows ARM64 support and NuGet signing. (#​27294)
• Testing: Updated BaseTester to support plugin EPs with both compiled nodes and registered kernels. (#​27176)
• Telemetry: Added service name and framework name to telemetry events for better usage understanding on Windows. (#​27252, #​27256)

Full Changelog: v1.24.1...v1.24.2

Contributors

@​tianleiwu, @​hariharans29, @​edgchen1, @​xiaofeihan1, @​adrianlizarraga, @​angelser, @​angelserMS, @​ankitm3k, @​baijumeswani, @​bmehta001, @​ericcraw, @​eserscor, @​fs-eire, @​guschmue, @​mc-nv, @​qjia7, @​qti-monumeen, @​titaiwangms, @​yuslepukhin

1.24.1

📢 Announcements & Breaking Changes

Platform Support Changes

• Python 3.10 wheels are no longer published — Please upgrade to Python 3.11+
• Python 3.14 support added
• Free-threaded Python (PEP 703) — Added support for Python 3.13t and 3.14t in Linux (#​26786)
• x86_64 binaries for macOS/iOS are no longer provided and minimum macOS is raised to 14.0

API Version

• ORT_API_VERSION updated to 24 (#​26418)

---

✨ New Features

🤖 Execution Provider (EP) Plugin API

A major infrastructure enhancement enabling plugin-based EPs with dynamic loading:

• Initial kernel-based EP support (#​26206)
• Weight pre-packing support for plugin EPs (#​26754)
• EP Context model support (#​25124)
• Control flow kernel APIs (#​26927)
• OrtKernelInfo APIs for kernel-based plugin EPs (#​26803)

🔧 Core APIs

• OrtApi::CreateEnvWithOptions() and OrtEpApi::GetEnvConfigEntries() (#​26971)
• EP Device Compatibility APIs (#​26922)
• External Resource Importer API for D3D12 shared resources (#​26828)
• Session config access from KernelInfo (#​26589)

📊 Dependencies & Integration

• ONNX upgraded to 1.20.1 (#​26579)
• Protobuf updated from 3.20.3 → 4.25.8 (#​26910)
• CUDA Graph enabled by default (#​26929)

---

🖥️ Execution Provider Updates

NVIDIA

• CUDA EP: Flash Attention updates, GQA kernel fusion, BF16 support for MoE/qMoE/MatMulNBits, CUDA 13.0 support
• TensorRT EP: Upgraded to TensorRT 10.14, automatic plugin loading, NVFP4 custom ops
• TensorRT RTX EP: RTX runtime caching, CUDA graph support, BFloat16, memory-mapped engines

Qualcomm QNN EP

• QNN SDK upgraded to 2.42.0 with new ops (RMSNorm, ScatterElements, GatherND, STFT, RandomUniformLike)
• Gelu pattern fusion, LPBQ quantization support, ARM64 wheel builds, v81 device support

Intel & AMD

• OpenVINO EP: Upgraded to 2025.4.1
• VitisAI EP: External EP loader, compiled model compatibility API
  ... (truncated)

1.23.2

1.23.1

What's Changed

• Fix Attention GQA implementation on CPU (#​25966)
• Address edge GetMemInfo edge cases (#​26021)
• Implement new Python APIs (#​25999)
• MemcpyFromHost and MemcpyToHost support for plugin EPs (#​26088)
• [TRT RTX EP] Fix bug for generating the correct subgraph in GetCapability (#​26132)
• add session_id_ to LogEvaluationStart/Stop, LogSessionCreationStart (#​25590)
• [build] fix WebAssembly build on macOS/arm64 (#​25653)
• [CPU] MoE Kernel (#​25958)
• [CPU] Block-wise QMoE kernel for CPU (#​26009)
• [C#] Implement missing APIs (#​26101)
• Regenerate test model with ONNX IR < 12 (#​26149)
• [CPU] Fix compilation errors because of unused variables (#​26147)
• [EP ABI] Check if nodes specified in GetCapability() have already been assigned (#​26156)
• [QNN EP] Add dynamic option to set HTP performance mode (#​26135)

Full Changelog: microsoft/onnxruntime@v1.23.0...v1.23.1

1.23.0

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

1.22.2

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

1.22.1

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

1.22

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.
    ... (truncated)

1.21.1

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

1.21.0

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).

... (truncated)

1.20.2

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

Commits viewable in compare view.

[dependabot]

Looks like Microsoft.ML.OnnxRuntime is no longer a dependency, so this is no longer needed.