[Perf] Windows/x64: 1 Improvement on 7/3/2026 8:55:45 AM +00:00

### Run Information

Name | Value
-- | --
Architecture | x64
OS | Windows 10.0.22631
Queue | ViperWindows
Baseline | [d3d091ef0dde723768cabb7fd2038894399dbd95](https://github.com/dotnet/sdk/commit/d3d091ef0dde723768cabb7fd2038894399dbd95)
Compare | [62e5e207d82113e873aedeb34429f809c4700aae](https://github.com/dotnet/sdk/commit/62e5e207d82113e873aedeb34429f809c4700aae)
Diff | [Diff](https://github.com/dotnet/sdk/compare/d3d091ef0dde723768cabb7fd2038894399dbd95...62e5e207d82113e873aedeb34429f809c4700aae)
Configs | CompilationMode:tiered, RunKind:imagesharp

### Improvements in SixLabors.ImageSharp.Benchmarks.Codecs.Jpeg.DecodeJpeg

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

• [JpegProgressiveNonInterleaved420 - Duration of single invocation]()
• 📝 - [Benchmark Source]()
• [ADX - Test Multi Config Graph]()

![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 'SixLabors.ImageSharp.Benchmarks.Codecs.Jpeg.DecodeJpeg*'
```

### SixLabors.ImageSharp.Benchmarks.Codecs.Jpeg.DecodeJpeg.JpegProgressiveNonInterleaved420

#### 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 src/benchmarks/real-world/ImageSharp/Codecs/Jpeg/DecodeJpeg.cs at lines 63-64, then run the provided benchmarks_ci.py command with the JPEG DecodeJpeg filter. Compare the Windows/x64 baseline and test results using the linked report and history page. Done means the reported performance change is understood and its follow-up is identified.

Written by the indexing model from the issue text.