ImageLayered turns flat images into named, editable layers. Precision mode decomposes up to 16 layers, results export as transparent PNGs, and a built-in AI generator creates new artwork. The core mod
Separate any image into editable transparent layers with AI. Extract subjects, text, objects, and backgrounds as individual RGBA layers.
Who it is for
Designers, developers, marketers and content teams who need to recover, edit or localize flattened images, or prepare transparent PNG elements for web and app d
Problem it solves
Flattened images lose their structure. Anyone who receives a flat PNG or JPG cannot edit individual elements, so teams waste time recreating assets from scratch or settling for cropped patches.
The solution
ImageLayered decomposes a flat image into individual, named layers automatically. You can inspect each layer, edit it, and export transparent PNGs — plus generate new layered artwork with the built-in AI generator.
What makes it unique
Layer decomposition goes up to 16 layers in Precision mode, layers come back named for direct use in design workflows, and the core model (Qwen-Image-Layered) is open source under Apache 2.0 — rare transparency for this kind of tool.
Features1 listed
Named, editable layers
Decomposes a flat image into individual named layers you can inspect and re-export.
Details
Platforms
Web
Pricing
Freemium
Built for
Designers, developers, marketers and content teams who need to recover, edit or localize flattened images, or prepare transparent PNG elements for web and app d
In IndieTools' mobile lab test on November 12, 2026, the ImageLayered website scored 85 out of 100 (needs improvement). Largest Contentful Paint took 4.05 s, rated poor. It placed #913 overall in the finalized week 2026-W45.
Measured (UTC)
LCPLargest Contentful Paint
4.05 s
Poor
TBTTotal Blocking Time
46 ms
Good
CLSCumulative Layout Shift
0.000
Good
FCPFirst Contentful Paint
1.05 s
Good
Ranked #913 overall in 2026-W45, best #177.
ImageLayered lab metrics
Speed metrics for ImageLayered, measured November 12, 2026
Metric
Result
Status
Trend
Mobile lab testMid-range phone on a throttled 4G connection, two runs averaged. Changes compare with the run on Nov 11.
Performance score
Needs improvementUp 3 points
85 / 100
Needs improvementUp 3 points
First Contentful PaintFCP
GoodAbout the same
1.05 s
GoodAbout the same
Largest Contentful PaintLCP
Poor450 ms faster
4.05 s
Poor450 ms faster
Speed IndexSI
Needs improvement125 ms faster
3.83 s
Needs improvement125 ms faster
Total Blocking TimeTBT
GoodAbout the same
46 ms
GoodAbout the same
Cumulative Layout ShiftCLS
GoodAbout the same
0.000
GoodAbout the same
Unthrottled observationsTimed on the test machine's own fast connection, so they read lower than the lab metrics above.
Page loadLoad
42 ms faster
985 ms
42 ms faster
Server responseTTFB
About the same
4 ms
About the same
ImageLayered performance history
55 comparable mobile lab runs since September 27, 2026. Choose a metric and a range, then move along the line to read each run.
ImageLayered Speed ranking
Weekly Speed standing for ImageLayered
Weekly standingLatest finalized week 2026-W45. Bests cover the last 52 finalized weeks.
Stored lab observations from controlled test runs, not real-user Core Web Vitals or a guarantee of search rankings. Weekly standings remain attached to their finalized edition.Method psi-mobile-two-sample-mean-v1, 2 samples per reading. Lab results can vary between runs.
Model difference+3. DR4 is 3 points higher than DR3.
Measured · imagelayered.com
What do DR4, DR3 and the model difference mean?
DR4:
Ahrefs' newer model. It gives more weight to links from sites with organic search traffic and rates a subdomain on its own links.
DR3:
The previous model, shown in the Ahrefs app until 1 December 2026.
Model difference:
DR4 minus DR3 for the same domain. The models calculate differently, so this is not growth or a drop; the “since” lines compare each model with itself.
