Environment:Dotnet Machinelearning Platform Architecture Support
| Knowledge Sources | |
|---|---|
| Domains | Infrastructure, Platform_Support |
| Last Updated | 2026-02-09 11:00 GMT |
Overview
Platform and CPU architecture requirements for ML.NET, with x64 as primary, partial ARM64/Apple M1 support, and limited 32-bit Windows support.
Description
ML.NET operates across multiple platforms and architectures with varying levels of component support. The x64 architecture has full support across all platforms. ARM64/Apple M1 support is available for training and inference but excludes several native-dependent components. 32-bit Windows has limited support excluding TensorFlow and LightGBM. Blazor WebAssembly has restricted support excluding most native components.
Usage
Use this environment definition to determine which ML.NET components are available on your target deployment platform. Check the compatibility matrix before selecting trainers or transforms in your pipeline to avoid runtime failures on non-x64 architectures.
System Requirements
| Category | Requirement | Notes |
|---|---|---|
| OS | Windows 10+, Linux (kernel 5.15+ recommended), macOS 10.13+ | Cross-platform |
| Architecture | x64 (primary), ARM64, x86 (Windows only) | Component availability varies |
| RAM | 2GB minimum | More for large datasets |
Dependencies
Linux Specific
- `libc` >= 2.23 (required for ONNX Runtime and TorchSharp)
macOS Specific
- macOS deployment target: 13.0
- Homebrew for package management recommended
Credentials
No credentials required for platform support.
Quick Install
# Check your architecture
dotnet --info | grep "RID"
# Verify libc version on Linux (must be >= 2.23 for ONNX/TorchSharp)
ldd --version
Code Evidence
Architecture detection for native code from `src/Microsoft.ML.FastTree/Dataset/IntArray.cs:40`:
public static bool UseFastTreeNative => RuntimeInformation.ProcessArchitecture == Architecture.X64 ||
RuntimeInformation.ProcessArchitecture == Architecture.X86;
OneDal x64-only check from `src/Microsoft.ML.OneDal/OneDalUtils.cs:24`:
if (System.Runtime.InteropServices.RuntimeInformation.ProcessArchitecture ==
System.Runtime.InteropServices.Architecture.X64)
ONNX Runtime libc check from `test/Microsoft.ML.TestFrameworkCommon/Attributes/OnnxFactAttribute.cs:28-29`:
// ONNX Runtime requires Linux with libc >= 2.23
TorchSharp 64-bit requirement from `test/Microsoft.ML.TestFrameworkCommon/Attributes/TorchSharpFactAttribute.cs:16`:
// TorchSharp: 64-bit only, requires libc >= 2.23 on Linux
ARM module exclusion from `Directory.Build.targets:33-38`:
<!-- Excluded on ARM: MklImports, CpuMathNative, FastTreeNative, SymSgdNative, MklProxyNative -->
Common Errors
| Error Message | Cause | Solution |
|---|---|---|
| `DllNotFoundException: FastTreeNative` | Running on ARM64 where FastTreeNative is not available | Use managed-only trainers (SDCA, LightGBM if compiled for ARM) |
| `GLIBC_2.23 not found` | Linux libc version too old | Upgrade to Ubuntu 16.04+ or equivalent with libc >= 2.23 |
| `System.PlatformNotSupportedException` | Component not supported on current platform | Check platform limitations matrix and switch to supported component |
Compatibility Notes
| Component | x64 | ARM64/Apple M1 | 32-bit Windows | Blazor WASM |
|---|---|---|---|---|
| Symbolic SGD | Supported | Not supported | Supported | Not supported |
| TensorFlow | Supported | Not supported | Not supported | Not supported |
| OLS Regression | Supported | Not supported | Supported | Not supported |
| TimeSeries SSA | Supported | Not supported | Supported | Not supported |
| TimeSeries SrCNN | Supported | Not supported | Supported | Not supported |
| ONNX | Supported | Inference only | Supported | Not supported |
| LightGBM | Supported | Can compile from source | Not supported | Not supported |
| LDA | Supported | Supported | Supported | Not supported |
| Matrix Factorization | Supported | Supported | Supported | Not supported |