[Perf] Windows/x64: 1 Improvement on 6/30/2026 2:04:55 PM +00:00

### Run Information

Name | Value
-- | --
Architecture | x64
OS | Windows 10.0.22621
Queue | Galaxy
Baseline | [3c8aafcb84d524fa331e238350bd0ba287a78ed8](https://github.com/dotnet/sdk/commit/3c8aafcb84d524fa331e238350bd0ba287a78ed8)
Compare | [b12fcac0dd6a8b40d74536c858139acfcca60e89](https://github.com/dotnet/sdk/commit/b12fcac0dd6a8b40d74536c858139acfcca60e89)
Diff | [Diff](https://github.com/dotnet/sdk/compare/3c8aafcb84d524fa331e238350bd0ba287a78ed8...b12fcac0dd6a8b40d74536c858139acfcca60e89)
Configs | CodeGenType:R2R, CompilationMode:tiered, RunKind:maui_scenarios_android, RuntimeType:coreclr

### Improvements in Device Startup - .NET Android Default Template NoAnimation

Benchmark | Baseline | Test | Test/Base | Test Quality | Edge Detector | Baseline IR | Compare IR | IR Ratio
-- | -- | -- | -- | -- | -- | -- | -- | --
|

• [NET Android Default Template NoAnimation - Generic Startup]()
• [ADX - Test Multi Config Graph]()

[Test Report]()

### Repro
General Docs link: https://github.com/dotnet/performance/blob/main/docs/benchmarking-workflow-dotnet-runtime.md

```cmd
git clone https://github.com/dotnet/performance.git
py .\performance\scripts\benchmarks_ci.py -f net8.0 --filter 'Device Startup - .NET Android Default Template NoAnimation*'
```

### Device Startup - .NET Android Default Template NoAnimation

#### ETL Files

#### Histogram

#### JIT Disasms

### Docs

[Profiling workflow for dotnet/runtime repository](https://github.com/dotnet/performance/blob/master/docs/profiling-workflow-dotnet-runtime.md)
[Benchmarking workflow for dotnet/runtime repository](https://github.com/dotnet/performance/blob/master/docs/benchmarking-workflow-dotnet-runtime.md)

Start with the benchmark command in the Repro section and the `scripts/benchmarks_ci.py` entry point, using the reported Device Startup filter. Compare the linked baseline and test reports, then inspect the benchmarking workflow documentation for how to validate the result. Done requires determining whether the measured improvement is expected and identifying a concrete, reproducible issue before making a change.

Written by the indexing model from the issue text.