[Perf] Linux/arm64: 1 Improvement on 6/27/2026 1:09:28 AM +00:00

### Run Information

Name | Value
-- | --
Architecture | arm64
OS | azurelinux 3.0
Queue | CobaltAzureLinux
Baseline | [eb60eb48998e0f79aee7217ef8faf9ba98cdb30a](https://github.com/dotnet/runtime/commit/eb60eb48998e0f79aee7217ef8faf9ba98cdb30a)
Compare | [ac17f52074f3a800bbf3cdd616eb61c315e1af1e](https://github.com/dotnet/runtime/commit/ac17f52074f3a800bbf3cdd616eb61c315e1af1e)
Diff | [Diff](https://github.com/dotnet/runtime/compare/eb60eb48998e0f79aee7217ef8faf9ba98cdb30a...ac17f52074f3a800bbf3cdd616eb61c315e1af1e)
Configs | CompilationMode:tiered, R2RType:r2r_interpreter, RunKind:micro

### Improvements in System.Collections.RemoveFalse<Guid>

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

• [Dictionary - 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 'System.Collections.RemoveFalse*'
```

### System.Collections.RemoveFalse<Guid>.Dictionary(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/Remove/RemoveFalse.cs at lines 54-63 and run the provided benchmarks_ci.py command for the System.Collections.RemoveFalse filter. Compare the linked baseline and test reports for the Linux/arm64 configuration; done means the reported performance improvement has been investigated and the relevant follow-up is identified.

Written by the indexing model from the issue text.