Flutter Performance

Measure a reproducible flow before changing code. Debug-mode timing is not release-performance evidence.

Establish evidence

Record the target device, Flutter version, build mode, flow, dataset, and metric. Reproduce in profile mode on representative hardware when the issue is user-facing.

Diagnose by symptom

• Frame jank: inspect UI/raster timing, expensive build/layout/paint, shader or image work.
• Excess rebuilds: inspect state subscription scope and widget identity before adding const mechanically.
• Slow startup: trace initialization and defer work not required for first useful frame.
• Memory growth: compare repeated-flow snapshots and find retained ownership, listeners, controllers, or caches.
• Large binaries: use Flutter's app-size analysis and compare like-for-like release artifacts.
• CPU-heavy Dart: use timeline/CPU profiling and consider isolates only after locating the work.

Prefer removing or moving work over caching everything. Bound caches and preserve correctness.

Load profile and frame analysis for frame, CPU, image, rebuild, or web-rendering investigations. Load memory, startup, and size for retention, first-useful-frame, or artifact-size work.

Verification

Repeat the same scenario after the change and report before/after evidence with variance. Run correctness tests because performance changes often alter lifecycle or caching behavior.

Sources

• Flutter performance
• DevTools performance view