Microsoft has published KB5096141, an automatic Windows Update package that updates the AMD MIGraphX Execution Provider to version 2.2605.1.0 for Windows 11 version 26H1 devices with the latest cumulative update installed, listing it in Update history as a Windows ML Runtime AMD component. The support note is brief, but the signal is larger than the changelog. Microsoft is treating local AI acceleration as something Windows services directly, not as a loose pile of app runtimes and vendor downloads. For AMD users and IT teams, that makes the machine-learning stack part of the operating system’s maintenance surface.
KB5096141 is not a Radeon driver release, and it is not a feature update dressed in AI branding. It updates a Windows ML execution provider: the layer that lets ONNX Runtime and Windows machine-learning workloads hand supported model operations to AMD GPU hardware through AMD’s MIGraphX inference engine.
That sounds obscure because, for most users, it is. Execution providers are not apps, taskbar buttons, or settings pages. They are the plumbing between a model and the silicon asked to run it. But Windows has spent decades proving that boring plumbing becomes strategically important the moment enough software depends on it.
The important phrase in Microsoft’s note is “downloaded and installed automatically from Windows Update.” That means this component is now on the same operational rails as other Windows-serviced parts of the platform. The update replaces a previous MIGraphX package, KB5089171, moving the component from the prior 2.2604-era release to 2.2605.1.0.
This is the kind of update that looks tiny in a help article and large in a systems diagram. Microsoft, AMD, and app developers are converging on a model where local inference is not merely a library bundled inside each application. It is increasingly a capability the OS discovers, updates, brokers, and exposes.
MIGraphX is AMD’s graph inference engine for accelerating supported model operations on AMD GPUs. In this Windows ML context, the MIGraphX Execution Provider gives Windows applications a vendor-specific AMD acceleration path without every developer having to reinvent the same hardware dispatch logic.
That does not mean every ONNX model suddenly flies on every AMD GPU. Execution providers have requirements, supported operation sets, driver expectations, and fallback behavior. If a provider cannot handle part of a graph, runtime policy may split work across providers or fall back to a more general path.
That is why servicing matters. Local AI performance is not a single switch labeled “GPU acceleration.” It is a stack: model format, runtime, execution provider, compiler, driver, firmware, and hardware capabilities. A weak link in that chain can turn a flashy AI feature into a hot laptop fan and a CPU-bound workload.
Microsoft’s decision to distribute provider updates through Windows Update is an attempt to tame that complexity. Instead of requiring each app to ship a frozen acceleration backend, Windows can keep the shared component fresher. That is good for developers, but it also moves responsibility closer to the platform owner.
That makes KB5096141 easy to misread. If you are on Windows 11 24H2 or 25H2 and do not see it, that does not necessarily indicate a broken update channel. It is tied to a specific Windows release branch and device generation strategy.
But the component model is not narrow. Microsoft’s Windows ML documentation already positions execution providers as dynamically available pieces that can be downloaded and updated depending on device and driver compatibility. CPU and DirectML remain broad foundations, while vendor-specific providers such as AMD MIGraphX target more specialized acceleration paths.
The 26H1 boundary therefore looks less like a limitation of ambition and more like controlled deployment. Microsoft is not trying to flip every Windows PC into the same AI hardware configuration overnight. It is building a serviced runtime layer that can follow the hardware where it makes sense.
For OEM systems, especially those marketed around AI performance, that approach is attractive. A new laptop can ship with a known Windows build, a compatible AMD stack, and an update channel for the provider that apps will rely on. For IT departments, it also means yet another component whose behavior can change through the normal servicing pipeline.
That small breadcrumb matters because AI runtime components are otherwise easy to lose track of. A user may notice only that an app is faster, slower, or different after an update. An administrator needs a way to connect that behavior to a servicing event.
The update history entry gives support desks a starting point. If a local inference workload changes behavior on a fleet of AMD-equipped 26H1 machines, KB5096141 becomes part of the timeline. It is not proof of causality, but it is evidence that the acceleration layer changed.
That distinction is important in enterprise troubleshooting. Windows Update is already crowded with cumulative updates, driver packages, Defender platform updates, Store app updates, Edge updates, and firmware deliveries. AI runtime packages add another layer to the matrix.
The smart operational move is not panic. It is inventory. Organizations experimenting with Windows ML or ONNX Runtime workloads should know which devices have which providers, which driver versions, and which apps are using vendor-specific acceleration. Without that baseline, every AI performance regression becomes guesswork.
MIGraphX inside Windows ML helps simplify that story. It gives AMD a first-class execution provider in the Microsoft-backed runtime path, with Windows Update carrying at least some of the servicing load. That is not the same as saying AMD has solved every developer pain point, but it is a more coherent distribution model than expecting each application to carry its own complete acceleration stack.
It also reflects a broader split in local AI hardware. NPUs are increasingly marketed for efficient background inference, camera effects, recall-like indexing, and lightweight model execution. GPUs still matter for larger parallel workloads and model classes that benefit from graphics-class compute. A Windows device may have both, and the runtime needs to choose intelligently.
For AMD systems, MIGraphX targets GPU acceleration, while other providers may target AMD’s NPU path or broader DirectML compatibility. The result is a layered set of options rather than a single “AMD AI” button. That is more accurate technically, but harder to explain to users.
The practical effect of KB5096141 is therefore modest but meaningful. It does not promise a new consumer feature. It refreshes the component that may make some local ONNX workloads faster, more compatible, or more stable on supported AMD GPU hardware.
A serviced provider model lets developers ask the OS what acceleration paths exist and choose accordingly. That reduces installer bloat and allows Microsoft and silicon vendors to improve performance after an app ships. It also creates a more Windows-native route for AI features that are not tied to a cloud API.
But there is a tradeoff. Developers give up some control when the operating system updates a component underneath them. An app tested against one provider version may encounter different behavior after Windows Update installs another. In theory, runtime compatibility contracts reduce that risk; in practice, anyone who has maintained GPU-accelerated software knows that driver-adjacent layers can be temperamental.
This is where Microsoft’s documentation and versioning discipline will matter. If execution providers become routine Windows components, developers need predictable release notes, compatibility matrices, rollback guidance, and clear failure modes. A support page that says “includes improvements” is enough for consumers, but not enough for serious production planning.
The deeper challenge is observability. Apps and administrators need to know whether a model ran on MIGraphX, DirectML, CPU, or another provider; whether the graph was partially accelerated; and whether fallback occurred silently. Without that visibility, the promise of hardware acceleration becomes difficult to validate.
AI runtime updates are not security patches in the usual sense, but they can affect application behavior. They may change performance characteristics, numerical behavior, memory use, device selection, compatibility with certain models, or error paths. That matters in environments using local inference for document processing, imaging, accessibility, data classification, or line-of-business workflows.
The risk is not that KB5096141 is dangerous. There is no public indication of that. The risk is that organizations treat AI acceleration as invisible infrastructure until an app depends on it. By then, the patch cadence, testing process, and telemetry may already be behind the curve.
This is especially relevant because Windows Update can install the package automatically on eligible systems. Automatic delivery is a benefit for security, consistency, and consumer simplicity. It is also a governance question when the component affects workloads that may be performance-sensitive or validation-sensitive.
For managed environments, the response should be boring and disciplined. Track the package. Test representative workloads. Watch for changes in inference latency and provider selection. Document which device classes are eligible. Treat the AI runtime like any other dependency that can influence production behavior.
That kind of sparse changelog is common for small support articles, but AI infrastructure deserves better. The audience for this component is not just ordinary users. It includes developers shipping ONNX models, OEMs validating device images, administrators managing Windows Update behavior, and enthusiasts trying to understand why a workload now chooses one provider over another.
A vague “improvements” line also makes it harder to separate vendor positioning from observed impact. If a model runs faster after the update, was that because MIGraphX improved graph optimization, because the app changed, because a driver changed, or because Windows selected a different provider? If it runs slower, the same uncertainty applies.
The opacity is not unique to Microsoft or AMD. Much of the AI acceleration world is still moving faster than its documentation culture. Silicon vendors want to ship performance gains quickly. OS vendors want to abstract complexity. Developers want stable targets. Users want everything to work without learning what an execution provider is.
KB5096141 sits right in the middle of that tension. It is a small update, but it belongs to a stack that needs adult supervision as it becomes more central to everyday computing.
That split is likely to define Windows AI for the next few years. The OS needs a general path that works across hardware, and it needs specialized paths that make premium silicon worth buying. DirectML supplies the former; providers such as MIGraphX point toward the latter.
For users, the distinction will mostly be invisible. They will install an app and expect it to run. Under the surface, the app or runtime may decide whether the best path is CPU, DirectML, MIGraphX, an NPU provider, or some combination.
For developers, the distinction is strategic. A broad compatibility path reduces support burden, while a vendor-tuned provider can unlock better performance for certain devices. The winning apps will likely be the ones that can adapt gracefully, not the ones that assume one accelerator path always exists.
This is why Microsoft’s provider catalog approach is significant. It turns acceleration into something that can be discovered and updated rather than hard-coded. KB5096141 is one instance of that model in motion.
That has benefits. Hardware vendors can improve support after devices ship. Microsoft can keep runtime components aligned with Windows ML. Developers can rely on a common platform layer. Users can get fixes without hunting through vendor portals.
It also has costs. The more Windows Update carries AI components, the more update governance must expand to include them. Enthusiasts will want to know what changed. Enterprises will want rings, deferrals, reporting, and rollback options. Developers will want compatibility guarantees.
The old Windows servicing debate was about security fixes versus feature churn. The new one adds AI behavior to the mix. A cumulative update might secure the OS, a driver update might fix a display issue, and an execution provider update might alter how an app runs an image model locally. They all arrive through adjacent channels, and users experience them simply as “Windows changed.”
Microsoft’s challenge is to make that change trustworthy. That requires not only stable code, but clearer language. If AI runtime components are now part of Windows maintenance, their release notes should eventually look less like stubs and more like engineering records.
But it also should not be dismissed. The update shows how Microsoft intends to keep vendor AI acceleration current on supported Windows devices. The GPU, the runtime, and Windows Update are being tied together more tightly than they were in the traditional desktop software model.
For AMD, that is a chance to make Windows AI feel less experimental. For Microsoft, it is another step toward making local inference a platform capability. For administrators, it is a reminder that AI is becoming part of endpoint management whether or not the organization has formally adopted an “AI PC” strategy.
The least useful response is to treat this as just another inscrutable KB number. The more useful response is to recognize the pattern: AI components are entering the normal Windows lifecycle, and they will need the same scrutiny as drivers, runtimes, and other shared dependencies.
Microsoft Turns AI Acceleration Into Patchable Plumbing
KB5096141 is not a Radeon driver release, and it is not a feature update dressed in AI branding. It updates a Windows ML execution provider: the layer that lets ONNX Runtime and Windows machine-learning workloads hand supported model operations to AMD GPU hardware through AMD’s MIGraphX inference engine.That sounds obscure because, for most users, it is. Execution providers are not apps, taskbar buttons, or settings pages. They are the plumbing between a model and the silicon asked to run it. But Windows has spent decades proving that boring plumbing becomes strategically important the moment enough software depends on it.
The important phrase in Microsoft’s note is “downloaded and installed automatically from Windows Update.” That means this component is now on the same operational rails as other Windows-serviced parts of the platform. The update replaces a previous MIGraphX package, KB5089171, moving the component from the prior 2.2604-era release to 2.2605.1.0.
This is the kind of update that looks tiny in a help article and large in a systems diagram. Microsoft, AMD, and app developers are converging on a model where local inference is not merely a library bundled inside each application. It is increasingly a capability the OS discovers, updates, brokers, and exposes.
The Execution Provider Is Where AI Meets the Driver Stack
ONNX Runtime is designed around the idea that a model should not need to know every detail of the hardware underneath it. An app loads an ONNX model, ONNX Runtime builds an execution plan, and an execution provider handles the actual work on a CPU, GPU, NPU, or other accelerator when it can.MIGraphX is AMD’s graph inference engine for accelerating supported model operations on AMD GPUs. In this Windows ML context, the MIGraphX Execution Provider gives Windows applications a vendor-specific AMD acceleration path without every developer having to reinvent the same hardware dispatch logic.
That does not mean every ONNX model suddenly flies on every AMD GPU. Execution providers have requirements, supported operation sets, driver expectations, and fallback behavior. If a provider cannot handle part of a graph, runtime policy may split work across providers or fall back to a more general path.
That is why servicing matters. Local AI performance is not a single switch labeled “GPU acceleration.” It is a stack: model format, runtime, execution provider, compiler, driver, firmware, and hardware capabilities. A weak link in that chain can turn a flashy AI feature into a hot laptop fan and a CPU-bound workload.
Microsoft’s decision to distribute provider updates through Windows Update is an attempt to tame that complexity. Instead of requiring each app to ship a frozen acceleration backend, Windows can keep the shared component fresher. That is good for developers, but it also moves responsibility closer to the platform owner.
Windows 11 26H1 Is the Narrow Stage for a Bigger Play
KB5096141 applies to Windows 11 version 26H1, all editions, and requires the latest cumulative update for that release. That matters because 26H1 is not being framed as a broad feature upgrade for every existing Windows 11 PC. Microsoft has described it as scoped for new devices coming to market in early 2026 rather than as the mainstream annual feature update path for existing machines.That makes KB5096141 easy to misread. If you are on Windows 11 24H2 or 25H2 and do not see it, that does not necessarily indicate a broken update channel. It is tied to a specific Windows release branch and device generation strategy.
But the component model is not narrow. Microsoft’s Windows ML documentation already positions execution providers as dynamically available pieces that can be downloaded and updated depending on device and driver compatibility. CPU and DirectML remain broad foundations, while vendor-specific providers such as AMD MIGraphX target more specialized acceleration paths.
The 26H1 boundary therefore looks less like a limitation of ambition and more like controlled deployment. Microsoft is not trying to flip every Windows PC into the same AI hardware configuration overnight. It is building a serviced runtime layer that can follow the hardware where it makes sense.
For OEM systems, especially those marketed around AI performance, that approach is attractive. A new laptop can ship with a known Windows build, a compatible AMD stack, and an update channel for the provider that apps will rely on. For IT departments, it also means yet another component whose behavior can change through the normal servicing pipeline.
The Update History Entry Is the Admin’s First Clue
Microsoft says administrators and users can confirm installation through Settings, Windows Update, and Update history. After installation, the update should appear as “Windows ML Runtime AMD MIGraphX Execution Provider (KB5096141).”That small breadcrumb matters because AI runtime components are otherwise easy to lose track of. A user may notice only that an app is faster, slower, or different after an update. An administrator needs a way to connect that behavior to a servicing event.
The update history entry gives support desks a starting point. If a local inference workload changes behavior on a fleet of AMD-equipped 26H1 machines, KB5096141 becomes part of the timeline. It is not proof of causality, but it is evidence that the acceleration layer changed.
That distinction is important in enterprise troubleshooting. Windows Update is already crowded with cumulative updates, driver packages, Defender platform updates, Store app updates, Edge updates, and firmware deliveries. AI runtime packages add another layer to the matrix.
The smart operational move is not panic. It is inventory. Organizations experimenting with Windows ML or ONNX Runtime workloads should know which devices have which providers, which driver versions, and which apps are using vendor-specific acceleration. Without that baseline, every AI performance regression becomes guesswork.
AMD Gets a Cleaner Windows Story, But Not a Magic Wand
AMD has long had a more complicated Windows AI story than Nvidia’s CUDA-centered ecosystem. ROCm has improved, DirectML provides a broad Windows abstraction, and Ryzen AI adds NPU-specific capabilities, but developers have often had to navigate a messy distinction between what works on Linux, what works on Windows, what works on Radeon, and what works on specific integrated or discrete GPU generations.MIGraphX inside Windows ML helps simplify that story. It gives AMD a first-class execution provider in the Microsoft-backed runtime path, with Windows Update carrying at least some of the servicing load. That is not the same as saying AMD has solved every developer pain point, but it is a more coherent distribution model than expecting each application to carry its own complete acceleration stack.
It also reflects a broader split in local AI hardware. NPUs are increasingly marketed for efficient background inference, camera effects, recall-like indexing, and lightweight model execution. GPUs still matter for larger parallel workloads and model classes that benefit from graphics-class compute. A Windows device may have both, and the runtime needs to choose intelligently.
For AMD systems, MIGraphX targets GPU acceleration, while other providers may target AMD’s NPU path or broader DirectML compatibility. The result is a layered set of options rather than a single “AMD AI” button. That is more accurate technically, but harder to explain to users.
The practical effect of KB5096141 is therefore modest but meaningful. It does not promise a new consumer feature. It refreshes the component that may make some local ONNX workloads faster, more compatible, or more stable on supported AMD GPU hardware.
Developers Are Being Nudged Toward the OS Runtime
For Windows developers, the strategic message is hard to miss: Microsoft wants AI apps to target Windows ML and ONNX Runtime rather than shipping a bespoke inference universe every time. That makes sense. If every app bundles its own runtime, provider, compiler, and hardware compatibility assumptions, the platform becomes fragile and redundant.A serviced provider model lets developers ask the OS what acceleration paths exist and choose accordingly. That reduces installer bloat and allows Microsoft and silicon vendors to improve performance after an app ships. It also creates a more Windows-native route for AI features that are not tied to a cloud API.
But there is a tradeoff. Developers give up some control when the operating system updates a component underneath them. An app tested against one provider version may encounter different behavior after Windows Update installs another. In theory, runtime compatibility contracts reduce that risk; in practice, anyone who has maintained GPU-accelerated software knows that driver-adjacent layers can be temperamental.
This is where Microsoft’s documentation and versioning discipline will matter. If execution providers become routine Windows components, developers need predictable release notes, compatibility matrices, rollback guidance, and clear failure modes. A support page that says “includes improvements” is enough for consumers, but not enough for serious production planning.
The deeper challenge is observability. Apps and administrators need to know whether a model ran on MIGraphX, DirectML, CPU, or another provider; whether the graph was partially accelerated; and whether fallback occurred silently. Without that visibility, the promise of hardware acceleration becomes difficult to validate.
The Enterprise Risk Is Change Without Visibility
The most conservative reading of KB5096141 is that it is a routine component update. The more realistic enterprise reading is that it represents a new class of moving part.AI runtime updates are not security patches in the usual sense, but they can affect application behavior. They may change performance characteristics, numerical behavior, memory use, device selection, compatibility with certain models, or error paths. That matters in environments using local inference for document processing, imaging, accessibility, data classification, or line-of-business workflows.
The risk is not that KB5096141 is dangerous. There is no public indication of that. The risk is that organizations treat AI acceleration as invisible infrastructure until an app depends on it. By then, the patch cadence, testing process, and telemetry may already be behind the curve.
This is especially relevant because Windows Update can install the package automatically on eligible systems. Automatic delivery is a benefit for security, consistency, and consumer simplicity. It is also a governance question when the component affects workloads that may be performance-sensitive or validation-sensitive.
For managed environments, the response should be boring and disciplined. Track the package. Test representative workloads. Watch for changes in inference latency and provider selection. Document which device classes are eligible. Treat the AI runtime like any other dependency that can influence production behavior.
“Includes Improvements” Is Doing a Lot of Work
Microsoft’s support text says the update includes improvements to the MIGraphX Execution Provider AI component for Windows 11 version 26H1. It does not enumerate performance gains, bug fixes, supported model changes, security hardening, driver compatibility updates, or known issues.That kind of sparse changelog is common for small support articles, but AI infrastructure deserves better. The audience for this component is not just ordinary users. It includes developers shipping ONNX models, OEMs validating device images, administrators managing Windows Update behavior, and enthusiasts trying to understand why a workload now chooses one provider over another.
A vague “improvements” line also makes it harder to separate vendor positioning from observed impact. If a model runs faster after the update, was that because MIGraphX improved graph optimization, because the app changed, because a driver changed, or because Windows selected a different provider? If it runs slower, the same uncertainty applies.
The opacity is not unique to Microsoft or AMD. Much of the AI acceleration world is still moving faster than its documentation culture. Silicon vendors want to ship performance gains quickly. OS vendors want to abstract complexity. Developers want stable targets. Users want everything to work without learning what an execution provider is.
KB5096141 sits right in the middle of that tension. It is a small update, but it belongs to a stack that needs adult supervision as it becomes more central to everyday computing.
DirectML Still Matters Because Vendor Paths Cannot Cover Everything
It would be a mistake to read the MIGraphX update as a replacement for DirectML. DirectML remains the broad Windows graphics-backed acceleration path, useful precisely because it abstracts across a wide range of GPUs. Vendor-specific providers can offer deeper hardware-specific optimization, but they usually come with narrower compatibility expectations.That split is likely to define Windows AI for the next few years. The OS needs a general path that works across hardware, and it needs specialized paths that make premium silicon worth buying. DirectML supplies the former; providers such as MIGraphX point toward the latter.
For users, the distinction will mostly be invisible. They will install an app and expect it to run. Under the surface, the app or runtime may decide whether the best path is CPU, DirectML, MIGraphX, an NPU provider, or some combination.
For developers, the distinction is strategic. A broad compatibility path reduces support burden, while a vendor-tuned provider can unlock better performance for certain devices. The winning apps will likely be the ones that can adapt gracefully, not the ones that assume one accelerator path always exists.
This is why Microsoft’s provider catalog approach is significant. It turns acceleration into something that can be discovered and updated rather than hard-coded. KB5096141 is one instance of that model in motion.
The Real Product Is the Servicing Model
The update’s version number, 2.2605.1.0, is less interesting than its delivery mechanism. Windows Update is the product story here. Microsoft is building a world in which AI capability is not simply installed at purchase and frozen until the next major OS release.That has benefits. Hardware vendors can improve support after devices ship. Microsoft can keep runtime components aligned with Windows ML. Developers can rely on a common platform layer. Users can get fixes without hunting through vendor portals.
It also has costs. The more Windows Update carries AI components, the more update governance must expand to include them. Enthusiasts will want to know what changed. Enterprises will want rings, deferrals, reporting, and rollback options. Developers will want compatibility guarantees.
The old Windows servicing debate was about security fixes versus feature churn. The new one adds AI behavior to the mix. A cumulative update might secure the OS, a driver update might fix a display issue, and an execution provider update might alter how an app runs an image model locally. They all arrive through adjacent channels, and users experience them simply as “Windows changed.”
Microsoft’s challenge is to make that change trustworthy. That requires not only stable code, but clearer language. If AI runtime components are now part of Windows maintenance, their release notes should eventually look less like stubs and more like engineering records.
The KB5096141 Lesson for AMD Windows PCs
KB5096141 should not be oversold. It is not a dramatic new Windows feature, and it does not guarantee that every AMD GPU owner will see a visible performance jump. It is scoped to Windows 11 version 26H1, requires the latest cumulative update, and updates a specific Windows ML component.But it also should not be dismissed. The update shows how Microsoft intends to keep vendor AI acceleration current on supported Windows devices. The GPU, the runtime, and Windows Update are being tied together more tightly than they were in the traditional desktop software model.
For AMD, that is a chance to make Windows AI feel less experimental. For Microsoft, it is another step toward making local inference a platform capability. For administrators, it is a reminder that AI is becoming part of endpoint management whether or not the organization has formally adopted an “AI PC” strategy.
The least useful response is to treat this as just another inscrutable KB number. The more useful response is to recognize the pattern: AI components are entering the normal Windows lifecycle, and they will need the same scrutiny as drivers, runtimes, and other shared dependencies.
The Patch Note That Points Past Itself
KB5096141 leaves Windows users with a few concrete facts and a larger architectural hint.- Microsoft is distributing AMD’s MIGraphX Execution Provider update automatically through Windows Update for eligible Windows 11 version 26H1 devices.
- The package updates the AMD provider to version 2.2605.1.0 and replaces the earlier KB5089171 release.
- The component is part of the Windows ML Runtime path used with ONNX Runtime to accelerate supported model operations on AMD GPU hardware.
- Users can verify installation in Windows Update history, where it should appear as the Windows ML Runtime AMD MIGraphX Execution Provider update.
- Administrators testing local AI workloads should track this package alongside cumulative updates, drivers, and app versions because it can affect the inference stack even when no user-facing feature appears to change.
References
- Primary source: Microsoft Support
Published: Tue, 26 May 2026 21:03:06 Z
- Official source: learn.microsoft.com
Windows ML execution providers
Learn which ONNX Runtime execution providers are available in Windows ML for accelerating local AI models across Windows PCs, and see their release history.learn.microsoft.com - Related coverage: onnxruntime.ai
AMD - MIGraphX
Instructions to execute ONNX Runtime with the AMD MIGraphX execution provideronnxruntime.ai
- Related coverage: amd.github.io
AMD - MIGraphX
Instructions to execute ONNX Runtime with the AMD MIGraphX execution provideramd.github.io
- Related coverage: windowsforum.com
KB5096141 Updates AMD MIGraphX Execution Provider via Windows Update
Microsoft has published KB5096141, an automatic Windows Update package that updates the AMD MIGraphX Execution Provider to version 2.2605.1.0 for Windows 11 version 26H1 devices with the latest cumulative update installed. The dry support note looks minor, but the delivery mechanism is the real...
windowsforum.com
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