Build an Android image-loading library as a request-processing system, not as a convenience wrapper around bitmap decoding. It must coordinate request identity, target lifecycle, fetching, size-aware decoding, transformations, caching, memory limits, and delivery. Glide and Coil show useful approaches to those responsibilities, but neither documentation nor the available evidence establishes a universal performance winner.
Why image loading needs a system
A compressed image can occupy far more memory after decoding. Android Developers illustrates the difference with a 4048 × 3036 image decoded as ARGB_8888: the resulting bitmap is about 48 MB by calculation, not a measurement that applies to every device or image. The decoded dimensions and pixel format, rather than the compressed file size alone, determine much of the bitmap’s memory cost. See Android’s bitmap guidance.
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In a scrolling screen, loading also competes with rendering and other app work. Fetching and decoding should not block the UI thread, while caching and reuse can avoid repeating expensive work as items appear and disappear. A library therefore has to manage work and resources across an entire request lifecycle, not merely turn a URL into a bitmap.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsDesign the request path
A useful mental model is a request moving from the caller, through a target-aware coordinator and data pipeline, into a cache or decoder, and finally back to the target. Glide describes fetching, decoding, displaying, resizing, caching, and resource pooling; Coil assigns request execution, fetching, decoding, and cache management to its ImageLoader. Those documented responsibilities suggest a practical architecture, while details such as request keys and lifecycle guarantees remain choices for the library being built.
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1. Define a request that identifies its result
Accept the source model and the options that can change the displayed output: target dimensions, transformations, placeholder and error behavior, and relevant cache or network policy. Give the request a stable identity that accounts for every result-changing option. There is no universal key format prescribed by Android, Glide, or Coil; the design must prevent a cached image for one size or transformation from being mistaken for another.
2. Coordinate work with the target
Bind a request to a view target or Compose state. In a recycled list, a target may be assigned a different item before its earlier work finishes, so the implementation should replace or cancel stale work and ensure an old completion cannot overwrite newer content. Coil documents request management, but exact cancellation and lifecycle behavior depend on the integration and should be defined and tested by the library.
3. Fetch from supported sources
Keep source resolution behind a fetcher or network layer. Depending on what the library implements, sources may include app resources, files, content URIs, and network responses. A pluggable networking interface can let applications supply their own stack; Glide documents flexible network-stack integration. Do not imply that every source type, authentication rule, or HTTP behavior comes for free: each supported path needs explicit handling.
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4. Decode near the display size, then transform
Inspect source dimensions and decode at a size close to what the target will render. Downsampling reduces the decoded bitmap’s memory requirement; perform fetching, decoding, and transformations away from the main thread. Android’s bitmap guidance covers decoding smaller images, and its Compose image optimization guidance recommends requesting the exact dimensions needed from the backend where possible.
5. Cache data and decoded resources deliberately
A source-data cache can save network work; a decoded or transformed-resource cache can save decoding and transformation work. A library may use both, but their keys and invalidation rules need to reflect the source, requested dimensions, and transformations that affect output. Bound cache capacity and define eviction rather than allowing image data to grow without limit. Android documents LruCache as a least-recently-used eviction pattern in its bitmap caching guidance.
Coil documents memory and disk caches owned by each ImageLoader. Its guidance favors a shared application loader because multiple loaders have separate caches and an OkHttpClient. For a library embedded in an app, Coil advises using coil-core and a privately managed loader rather than replacing the host application’s singleton. See Coil’s ImageLoader documentation and its FAQ.
6. Deliver state without stale updates
Expose loading, success, and failure to the target, and associate completion with the request that produced it. If a target has since received a newer request, an older result must not replace that newer content. This is a recommended race-avoidance property, not an automatic guarantee of any particular library; test it under cancellation, recycling, and out-of-order completion.
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Server resizing versus client downsampling
If the backend offers appropriately sized variants, requesting a close match can reduce transferred bytes as well as local disk and memory use. Android explicitly recommends exact-size backend requests where possible in its Compose optimization guidance. Client downsampling is still needed when source dimensions are fixed or no suitable server variant exists. The two approaches can complement each other: fetch a suitable variant, then decode it for the actual display target.
Source cache versus resource cache
Choose what each cache avoids. Retaining fetched bytes or files can avoid another network fetch; retaining decoded or transformed output can avoid repeating CPU-intensive processing. If output depends on dimensions or a transformation, resource identity must account for those inputs. Cache invalidation, eviction, and policy semantics are part of the library’s API contract, not details a caller should have to guess.
One loader or several
A shared loader can centralize cache reuse and network resources. Coil’s documented recommendation is one application-level ImageLoader for performance, since separate loaders own separate memory and disk caches and an OkHttpClient. A reusable library should not take over an application’s global loader; Coil recommends that library authors use coil-core with a privately managed loader instead.
Decide which extensibility is worth owning
Pluggable fetchers, decoders, and transformations make a library adaptable, but each extension adds questions: who owns its work, how cancellation behaves, which result options belong in cache keys, and how failures surface. Glide’s documented range—including images, video stills, animated GIFs, resizing, network-stack integration, and resource pooling—illustrates possible scope, not a requirement for a first release. If adding GIF or video-frame support, specify and test its decoder behavior and memory use independently.
Keep privacy and rights in the design too. Network sources may be authenticated or sensitive, and caching must respect the source’s applicable policy and the app’s data-handling needs. Define which requests may be persisted and how callers can control that behavior.
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| Dimension | Coil | Glide |
|---|---|---|
| Documented orientation | Kotlin-first, coroutine-backed, with Compose integration; ImageLoader executes requests and manages fetching, decoding, and caches. | Android image-loading and caching library focused on smooth scrolling; documents fetching, decoding, display, resizing, and resource pooling. |
| Documented format or source scope | The cited documentation establishes image loading and Compose integration; it does not establish a comparable exhaustive format list. | Project documentation lists images, video stills, and animated GIFs, and describes flexible network-stack integration. |
| Cache and loader considerations | Per-loader memory and disk caches; documentation favors one shared app loader and cautions libraries against replacing an application’s singleton. | Documents caching and resource pooling; the cited material does not state a directly comparable loader-sharing policy. |
These are documented design characteristics, not a controlled benchmark. Android’s Compose guidance says to choose an image-loading approach based on project requirements and performance constraints; it does not publish a direct Glide-versus-Coil test. Compare candidates against the app’s actual formats, UI integration, networking needs, cache controls, lifecycle requirements, dependency footprint, and representative scrolling workload. Measure on the target devices and workload before drawing a performance conclusion. See Android’s Compose image-loading guidance, Coil’s project documentation, and Glide’s project documentation.
Validate the design before expanding it
- Confirm that large sources are decoded close to the display size and that image work does not block the UI thread.
- Exercise fast scrolling and target reuse, including old requests completing after a target has moved to a new item.
- Check that cache identity changes when dimensions or transformations change, and that invalidation and eviction behave as documented.
- Test cancellation, failures, and each supported source type rather than assuming one successful URL fetch represents all paths.
- Measure memory, network traffic, and scrolling behavior for the app’s own images and devices before selecting a design or claiming a speed advantage.
Android’s Compose guide specifies API 21+ for the implementation discussed there; that minimum should not be generalized to every release, feature, or separately built image library. Check the support requirements of the exact versions and integrations you plan to ship.
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