Forcing every upload into JPEG can increase file size and damage colored text. In one author-reported test, a 1600×900 red-and-yellow poster grew from 126,373 bytes as PNG to 157,626 bytes as JPEG at quality 0.9, with a visible halo around red text. That is a useful warning, not a universal benchmark: results depend on image content, the original encoding, the encoder and its settings.
Why can a JPEG be bigger than the PNG it came from?
JPEG is not automatically smaller. It is a lossy format designed to exploit patterns in image data; it does not promise a smaller result for every source. Flat artwork, text and other images with sharp color boundaries may compress poorly when encoded as JPEG. The encoder can add color variation around those boundaries, leaving more data to encode than the original PNG needed.
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In the reported test, AsyncMonk’s upload tool drew each image to a canvas and requested image/jpeg through toBlob at quality 0.9. On a generated 1600×900 poster with red and yellow graphics and red and black text, the author measured a 126,373-byte PNG and a 157,626-byte JPEG. The test used an open-source Chromium 149 build on an Apple M4 Mac with 16 GB of memory. The author also measured CIE76 ΔE 7.11 in a narrow band around glyph edges and described a dirty halo around red text. These are that author’s measurements, not independently reproduced results or a general JPEG benchmark. Read the case report.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsPNG’s specification says, “There is no lossy compression in PNG.” That does not mean every PNG conversion preserves pixels: changing a full-color image to a reduced palette can quantize colors. But the PNG format itself does not use lossy compression. JPEG, by contrast, discards information during encoding, and that trade-off may not pay off in bytes for a particular graphic. PNG Specification, version 1.2.
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Why does red text look blurry or dirty after JPEG conversion?
JPEG commonly stores brightness and color information at different resolutions. Chroma subsampling reduces the spatial resolution of color channels; edges of saturated colors can therefore spread or blur even when luminance detail, such as black text, remains comparatively sharp. A red glyph against white or another contrasting color is a useful stress case because its boundary depends strongly on color detail.
The case report’s edge measurements changed with the requested quality. On that poster, quality 0.8 produced 120,501 bytes and edge ΔE 8.11; quality 0.99 produced 270,978 bytes and ΔE 6.35; and quality 1.0 produced 438,482 bytes and ΔE 0.19. In the author’s tests, Chromium used 4:2:0 subsampling through quality 0.99 and 4:4:4 at 1.0; Firefox 151 switched from 4:2:0 to 4:4:4 at 0.895. Those are observations for the tested browser builds, not portable thresholds or guarantees for release browsers. The author did not check release Chrome or Safari.
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Quality values are encoder controls, not a shared visual-quality scale across browsers and libraries. A higher setting can make a file much larger while only gradually improving a particular edge. In this test, the highest setting nearly removed the measured edge difference, but its output was far larger than the PNG. That does not establish that quality 1.0 is a sensible general fix.
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The author also tested a 1242×2688 PNG template image measuring 3,339,216 bytes. They report that browser JPEG output at qualities from 0.80 to 0.99 grew to 3.2 times the PNG size, while the red-text edge metric improved from 6.56 to 4.48. The result reinforces that a quality slider alone cannot be assumed to save bytes, but it remains one source image tested in one encoder environment. The report says photos were not tested, so its examples do not establish a general dividing line between photographs and graphics. Case report and measurements.
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How should you choose an output format?
Choose based on the actual image and delivery requirements, then compare encoded files. Format names and quality settings alone do not tell you which output will be smallest or look best.
- Keep PNG when: the image needs alpha transparency, pixel-precise text or hard-edged graphics, or the JPEG version visibly damages important edges. PNG supports a full alpha channel and does not use lossy compression.
- Consider JPEG when: the image is appropriate for lossy encoding and the actual output is smaller at acceptable visual quality. Inspect colored edges and small text rather than judging only overall appearance.
- Consider WebP when: your upload and delivery stack supports it and testing shows a useful result. WebP has both lossy and lossless paths: Google’s FAQ describes lossy WebP as 8-bit Y’CbCr 4:2:0 and lossless WebP as RGBA. Neither path guarantees a smaller file for every input. Google specifically warns that low-color lossless PNGs converted to lossy formats can gain colors through spatial downsampling and may become larger. Google WebP FAQ.
Transparency details can matter too. Google notes that simple lossless WebP encoder API defaults may change RGB values in fully transparent pixels; its advanced API’s exact option preserves those values. That concerns invisible pixels, not necessarily visible color changes. Google also notes that lossless WebP can be larger than its source in some conversions, including lossy-to-lossless conversions.
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How to test an upload pipeline before changing it
- Collect representative inputs. Include photos, screenshots, logos, flat illustrations, gradients and text-heavy graphics from the images your users actually upload. One poster cannot set a universal conversion rule.
- Encode with the real production path. Use the browser and version, library and encoder settings your upload flow will use. Record the source format, dimensions, output format and settings so another test is comparable.
- Compare byte sizes. Measure the source and output files directly. Keep a conversion only when it delivers the size or delivery benefit you need.
- Inspect likely failure points. View each result at its intended display size, then magnify small text and high-contrast colored edges—especially saturated red against white or another contrasting background.
- Check transparency and color management. Confirm whether alpha is required and whether profiles or other relevant metadata survive the conversion. A visually altered result may reflect more than the compression setting.
- Set a content-aware fallback. If a converted file is larger or visibly worse, preserve the original or choose another tested format rather than forcing the same JPEG rule on every upload.
Which encoder controls are worth checking?
Browser and library defaults can select different compression behavior, so a quality number alone is not enough to reproduce a result. If you use Pillow, its current stable documentation identifies version 12.3.0. Pillow’s JPEG save options use a quality range of 0–95 by default; the documentation advises avoiding values above 95 because they create large files with hardly any image-quality gain. It also allows explicit 4:4:4, 4:2:2 or 4:2:0 subsampling; if you do not set it, libjpeg or libjpeg-turbo determines the choice. When color management matters, preserve the ICC profile deliberately: Pillow says it is not retained unless passed to the save operation. Pillow image-format documentation.
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These controls make behavior more deliberate, not universally optimal. Test the exact combinations your pipeline can produce against representative source images, weighing file bytes, edge fidelity, transparency, profile retention and compatibility with your upload and delivery stack.
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