[Perf] Linux/x64: 1 Improvement on 8/11/2026 4:34:13 PM +00:00

### Run Information

Name | Value
-- | --
Architecture | x64
OS | ubuntu 22.04
Queue | ViperUbuntu
Baseline | [b470543f2f101c83205ac0a0e008c934be9774db](https://github.com/dotnet/runtime/commit/b470543f2f101c83205ac0a0e008c934be9774db)
Compare | [1fdccbc9c3690a80a9579bdc0e9be997db1ac0de](https://github.com/dotnet/runtime/commit/1fdccbc9c3690a80a9579bdc0e9be997db1ac0de)
Diff | [Diff](https://github.com/dotnet/runtime/compare/b470543f2f101c83205ac0a0e008c934be9774db...1fdccbc9c3690a80a9579bdc0e9be997db1ac0de)
Configs | CompilationMode:wasm, RunKind:micro, RuntimeType:coreclr

### Improvements in System.Collections.AddGivenSize<String>

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

• [ObservableCollection - 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 'System.Collections.AddGivenSize*'
```

### System.Collections.AddGivenSize<String>.ObservableCollection(Size: 512)

#### 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/micro/libraries/System.Collections/Add/AddGivenSize.cs at lines 126-135 and read the benchmarking workflow linked in the issue. Run the provided benchmarks_ci.py command for System.Collections.AddGivenSize, then compare the reported baseline and test results. Done means the performance change is understood and any resulting action is supported by benchmark evidence.

Written by the indexing model from the issue text.