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No single image compression method always looks best. Lossless compression reproduces the original image data exactly; lossy compression discards some information to make files smaller. Which result looks better depends on the image, encoder and settings, file-size target, transparency needs, and display context. To compare methods fairly, hold image dimensions constant and judge both visible quality and file size across photographs and graphics—not just one sample.

What “looks best” means in a compression comparison

There are two useful ways to compare compressed images, and they answer different questions:

  • Same file size: Keep the source image and dimensions fixed, then compare how much visible damage each method produces at a stated target size. This shows which method preserves more detail under a size constraint.
  • Similar perceived quality: Decide what level of visible change is acceptable, then compare the file sizes needed to reach it. State how that similarity was judged; it is not a self-evident measurement.

Do not compare formats using their quality-slider numbers as if those numbers shared a scale. Encoder controls and implementations differ. A setting of 80 in one encoder does not establish the same visual quality as 80 in another.

A meaningful visual comparison also needs more than one kind of source: a photograph with gradual tones, plus an image containing text, flat colors, thin lines, or sharp edges. A format that looks convincing on a photograph may show obvious artifacts around lettering or graphic edges.

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How lossless and lossy compression affect appearance

Lossless compression

Lossless compression preserves the image data so that decoding reconstructs it exactly. It is the safer choice when pixel-accurate reproduction matters, such as screenshots, diagrams, and line art. It does not guarantee the smallest file: the amount of compression depends on the image and format.

Lossy compression

Lossy compression removes information to reduce file size. On many photographs, the change can be difficult to notice at a suitable setting and normal viewing size. Artifacts are more likely to stand out around text, thin lines, high-contrast edges, and flat-color boundaries. Chroma subsampling can particularly affect high-contrast colored text.

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As MDN Web Docs puts it, “Compression can be lossy, discarding image data to get much smaller files, or lossless, reproducing the original exactly.” MDN’s image format guide explains the trade-off in the context of common web image types.

How the main image formats compare

Format Compression and typical use Visual considerations Relevant features
JPEG Lossy; a broadly supported fallback for photographs. At smaller sizes, lossy artifacts can show around edges and text. It is not a good fit when exact pixel reproduction or alpha transparency is needed. No alpha transparency channel.
PNG Lossless; useful for screenshots, diagrams, line art, and images that need transparency. Preserves image data exactly, but can produce larger files than a lossy option for photographic content. Broadly supported; supports transparency.
WebP Offers both lossy and lossless compression. Google reports WebP lossy files as 25–34% smaller than comparable JPEGs at equivalent SSIM quality, and lossless WebP as 26% smaller than PNG. These are Google-published comparisons, not guaranteed savings for every image, encoder, or setting. Supports transparency, animation, metadata, and color profiles. The lossless algorithm restores pixel values exactly, including color values for fully transparent pixels, according to RFC 9649; that statement applies to lossless WebP, not lossy WebP.
AVIF Supports lossy and lossless compression and can offer strong compression. Its result still depends on content and encoding settings; strong compression is not the same as a universal visual win. Check compatibility for the browsers and applications you need. web.dev’s image performance guide discusses delivery options such as a fallback.
SVG Vector format rather than a raster compression alternative. For diagrams and graphics that should remain sharp at different sizes, use the actual vector source where available instead of forcing a raster-format comparison. Appropriate for vector artwork, not a replacement for photographic raster images.

Google’s published figures are useful context, but they should not be read as a guarantee that WebP will look better or always be smaller on a particular image. Similarly, a 2023 paper by Dornauer and Felderer reported page-load-time improvements of 21% for WebP and 15% for AVIF compared with compressed JPEG in its evaluated setup. Those are results from that study’s setup, not universal forecasts for a website or evidence that one format looks best. The paper’s 4% WebP share refers to its observed web-image sample, not current global usage; its 41% figure for image data refers to the paper’s introduction and context. See the 2023 paper for its methodology and findings.

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Which method to choose for your image

  • Photographs where reducing bytes matters: Compare lossy JPEG, WebP, and AVIF at your target dimensions and a visually acceptable quality. Review the actual output rather than selecting by a slider number or format name.
  • Screenshots, diagrams, and text-heavy images: Start with lossless PNG or lossless WebP when exact edges and lettering matter. If you test lossy compression, inspect text and thin lines at the size people will actually see.
  • Transparency: Use a format and encoding mode that support it, such as PNG or WebP. JPEG does not provide an alpha channel.
  • Animation: WebP supports animation; verify that the target browsers and applications handle the chosen format.
  • Scalable diagrams or logos: Prefer the original SVG when it is available and suitable.
  • Mixed audiences or uncertain support: Offer a modern format with a fallback rather than assuming every client can display the same source.

For web delivery, a <picture> element can let a browser choose AVIF or WebP when supported and fall back to JPEG. The example below assumes you have generated the corresponding files at the same dimensions:

<picture>
  <source srcset="photo.avif" type="image/avif">
  <source srcset="photo.webp" type="image/webp">
  <img src="photo.jpg" alt="Description of the photograph">
</picture>

A practical way to make your own visual comparison

  1. Choose representative originals. Include at least one photograph and one graphic with small text, fine lines, or flat-color edges if those are part of your site.
  2. Keep dimensions and crop identical. Otherwise, a change in sharpness or file size may come from resizing rather than compression.
  3. Export each candidate using a documented encoder and setting. Compare formats at equal byte targets for a size-constrained decision, or adjust them until they look acceptably similar for a size-at-quality decision. Do not treat quality numbers from different encoders as equivalent.
  4. Inspect the details and the normal viewing size. Look closely for ringing, blockiness, color bleeding around text, lost fine detail, and transparency problems, then view the image at the size and background where it will appear.
  5. Record bytes as well as appearance. Keep the source, dimensions, output format, encoder, settings, and file size with your comparison. That makes the result useful for your own images instead of implying a universal winner.
  6. Check actual delivery compatibility. Test the browsers and applications your audience uses, and retain a suitable fallback where support is uncertain.

Tools such as Squoosh, ImageOptim, and image optimization services can help produce alternatives; web.dev recommends trying different compression levels because no one setting suits every image. The comparison still has to be made on the output you plan to publish, not on the tool’s label for a quality level. See web.dev’s image performance guidance.

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Using ScreenshotNeo to inspect a page with compressed images

ScreenshotNeo is a website screenshot API and MCP server, not an image compressor: use it to capture a rendered page when you want to inspect how your chosen image files appear in context. Its capture options include full-page screenshots and device presets. ScreenshotNeo also removes known consent banners, newsletter popups, and chat widgets before capture, with those steps individually configurable. Only clean shots are billed; bot checks or CAPTCHAs, blank pages, timeouts, failed loads, and cache hits cost nothing, and responses identify the page verdict and billing status in headers.

For agents, its MCP server provides take_screenshot, get_page_info, and capture_pdf. The free plan includes 1,000 shots per month with no card; paid plans start at $5 for 3,000 shots. All listed features are available on every plan. These captures can help review a rendered page, but they do not replace a controlled comparison of the source image files.

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Sign up free for 1,000 screenshots a month, with no card required.

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