Why Your Compose LazyColumn Still Stutters
Six hidden performance pitfalls in Jetpack Compose lists and how to fix them
1The scrolling illusion
Jank during scrolling isn't caused by the scroll itself but by earlier decisions in list implementation. When users scroll, Compose has minimal decisions left - the real costs were committed during list declaration, item shaping, and image decoding choices. These hidden costs manifest as frame drops during rapid scrolling, particularly noticeable on mid-range devices with slower networks. The article focuses on six specific optimization opportunities that address these root causes rather than surface-level symptoms.
2Key stability matters
Missing or unstable keys force Compose to rebuild items unnecessarily. When new items arrive (like in a chat feed), positional identification causes entire visible windows to recompose instead of reusing existing items. Stable keys combined with proper contentType declarations allow Compose to efficiently move items rather than rebuild them. Production implementations must ensure keys are truly stable and unique across the entire list, avoiding common pitfalls like using indexes, content hashes, or random UUIDs as keys.
3Nested scroll traps
Improperly nested scroll containers can completely defeat lazy loading. A common mistake occurs when wrapping a LazyColumn in a vertically scrolling Column to make headers scrollable - this gives the list unbounded height, causing immediate composition of all items. The correct approach uses a single LazyColumn with header items. Similar issues occur with horizontal LazyRows inside LazyColumn items, requiring careful state management to preserve scroll positions when items scroll out of view and return.
4First composition costs
Recomposition metrics hide the true cost of initial item composition. During rapid scrolling, the first composition of new items entering the viewport often exceeds frame budgets. Expensive operations like gradient calculations, markdown parsing, and complex modifier chains in item content contribute to this. Solutions include moving work to ViewModels, hoisting constants, and flattening layout hierarchies. Glassmorphism effects (blurs, large shadows) are particularly problematic as they incur per-frame draw costs.
5Image decoding overhead
Image handling causes more scroll jank than other issues combined, yet remains invisible to Compose tooling. Decoding full-resolution images during scroll frames triggers GC pauses and allocation churn. The fix involves requesting properly sized images (via backend resizing or client-side scaling), disabling animations during scroll, and ensuring proper caching. Fixed image dimensions before loading prevent layout shifts, and memory cache validation ensures decoded bitmaps are reused rather than re-decoded.
6Prefetch tuning
Default prefetch settings assume lightweight items and often prove inadequate for rich feed cards. The LazyLayoutCacheWindow API allows customization of prefetch distances, but requires careful balancing between performance and memory usage. Measurements should focus on worst-case devices, with prefetch distances typically optimized around 1.5 screens ahead. A common pitfall involves incorrectly tracking visibility - prefetched items may trigger effects like video autoplay before becoming visible to users.
7Debug vs release disparity
Debug builds significantly misrepresent Compose performance due to missing optimizations like R8 and baseline profiles. Without these, Compose runtime classes interpret or JIT on first use - exactly the code paths exercised during cold scrolling. Valid performance measurement requires release builds with proper signing, installed baseline profiles, and macrobenchmarking that focuses on P90/P99 frame times rather than averages. Baseline profile generation often delivers double-digit percentage improvements with zero code changes.
8Measurement methodology
Accurate performance assessment requires specific tooling and methodology. Composition tracing (rather than recomposition counts) reveals true first-composition costs. Valid testing requires release builds with R8 enabled, proper signing, and baseline profiles installed. Macrobenchmarks should use scrollAndMeasure-style interactions while monitoring frame timing metrics, with particular attention to percentile durations rather than averages. Many perceived performance issues disappear entirely when measured properly in release configurations.
9Optimization priority
The article recommends addressing issues in a specific order: first ensure proper keying and stable identities, then verify no nested scroll containers defeat laziness. Next optimize first-composition costs in items, followed by image handling improvements. Only then consider advanced techniques like prefetch tuning. Baseline profile generation should be implemented early as it often provides significant gains without code changes. Debug-build measurements should always be validated against release configurations.
10The stability tradeoff
Some optimizations involve balancing stability and performance. While making items fully stable (all params immutable) helps recomposition, it may push work into first composition. The solution often involves moving expensive operations upstream while keeping item APIs stable. Similarly, prefetch tuning trades memory usage for smoother scrolling. These decisions require measurement-driven iteration rather than theoretical optimization, focusing on real-world device performance under typical usage patterns.
11Tooling gaps
Current Compose tooling has significant blind spots for scroll performance analysis. Recomposition counts don't capture first-composition costs, and image decoding overhead remains completely invisible. Developers must combine multiple tools: composition tracing for initial costs, systrace for system-level issues, and custom benchmarks for holistic measurement. The article provides specific tracing techniques to identify which of the six issues affects a particular list, helping target optimization efforts effectively.
12Cultural shift needed
Solving Compose performance issues requires moving beyond superficial metrics to deeper understanding. Teams should prioritize proper measurement setups, share performance budgets, and treat jank as a critical bug rather than an inevitable compromise. The most effective optimizations often come from architectural decisions (like proper image handling) rather than micro-optimizations. This mindset shift, combined with the technical fixes outlined, can eliminate scroll jank while maintaining rich, complex UIs.
Original article: ProAndroidDev - Medium — Why Your Compose LazyColumn Still Stutters