[Perf] Linux/x64: 1 Improvement on 7/23/2026 11:22:19 AM +00:00

### Run Information

Name | Value
-- | --
Architecture | x64
OS | ubuntu 22.04
Queue | ViperUbuntu
Baseline | [7e07d48faae88ae9068a6afc91e7524b2112c0e7](https://github.com/dotnet/sdk/commit/7e07d48faae88ae9068a6afc91e7524b2112c0e7)
Compare | [d2b524965e50619e8db62ed35943981830e1008d](https://github.com/dotnet/sdk/commit/d2b524965e50619e8db62ed35943981830e1008d)
Diff | [Diff](https://github.com/dotnet/sdk/compare/7e07d48faae88ae9068a6afc91e7524b2112c0e7...d2b524965e50619e8db62ed35943981830e1008d)
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
-- | -- | -- | -- | -- | -- | -- | -- | --
|

• [JpegBaseline400 - 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
python3 .\performance\scripts\benchmarks_ci.py -f net8.0 --filter 'SixLabors.ImageSharp.Benchmarks.Codecs.Jpeg.DecodeJpeg*'
```

### SixLabors.ImageSharp.Benchmarks.Codecs.Jpeg.DecodeJpeg.JpegBaseline400

#### 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 source at src/benchmarks/real-world/ImageSharp/Codecs/Jpeg/DecodeJpeg.cs#L60-L61 and read the benchmarking workflow linked in the issue. Run the provided benchmarks_ci.py command with the DecodeJpeg filter on Ubuntu, then compare the reported baseline and test results. Done means the reported performance improvement is reproduced and understood.

Written by the indexing model from the issue text.