imgSquash

imgsquash image compressor FAQ’s

Frequently asked questions and other tips to get the most out of imgsquash

About imgsquash

What is ImgSquash?

ImgSquash is a fast, privacy-focused, in-browser image compression and optimization tool that supports AVIF, WebP, JPEG, PNG, and JPEG XL, with optional AI upscaling via Real-ESRGAN for higher-quality enlargements. By adopting next‑gen image formats like AVIF and WebP, ImgSquash helps reduce file sizes significantly while maintaining visual quality, improving page speed and Core Web Vitals for better SEO performance.

How does ImgSquash work?

  1. Upload images.
  2. Set format and quality parameters
  3. Wait for processing to complete
  4. Download your results.

All image processing runs locally in the browser using modern web technologies, so files are not uploaded to a server, preserving privacy and reducing latency. Local processing enables rapid compression, conversion, and AI upscaling workflows without relying on external APIs or server-side queues.

Who is ImgSquash for?

ImgSquash is ideal for web developers, SEO specialists, designers, marketers, photographers, and e‑commerce teams who need smaller, faster-loading images without noticeable quality loss and who value private, device-side processing. It’s built for teams optimizing Core Web Vitals, especially Largest Contentful Paint (LCP), via modern formats and streamlined bulk processing.

Features

Which image formats are supported?

ImgSquash supports AVIF, WebP, PNG, JPEG, and JPEG XL for conversion and compression, letting users fine-tune quality-to-size trade-offs for each use case. AVIF and WebP typically deliver superior compression at similar visual quality compared to legacy formats, making them strong defaults for web performance and SEO outcomes.

Does imgsquash support bulk processing?

Yes, ImgSquash supports batch conversion and compression to accelerate workflows and standardize output settings across many images. Device performance and browser capabilities influence batch limits since processing is local rather than server-based.

Is there AI upscaling available through the app?

Yes—ImgSquash offers AI-powered upscaling using Real-ESRGAN to restore detail and sharpness in low-resolution images before web optimization. Real-ESRGAN is widely used for practical image restoration and can be adapted to run efficiently in modern browsers using GPU acceleration where available.

Can I adjust quality settings?

Yes, configurable quality controls let users balance file size and visual fidelity per image or in bulk workflows, with best results when targeting AVIF/WebP for photos and WebP lossless/PNG for graphics and logos. Testing different settings by template type (e.g., product pages vs. blog) helps lock in the optimal quality-to-size profile for SEO and user experience.

Is it comparable to other in-browser optimizers?

Like other browser-based tools, ImgSquash processes locally for privacy and speed, while adding batch optimization and AI upscaling—features aligned with modern web performance practices. Local-first processing reduces dependency on external services and helps keep media workflows compliant and secure.

Privacy & Security

Are my uploaded images stored or used by imgsquash?

No—processing happens entirely in the browser, so images never leave the device, which enhances privacy and reduces compliance risk. Local processing also avoids server-side caches or logs that could inadvertently store sensitive media.

Is there metadata handling?

Optimization commonly removes unnecessary metadata (EXIF) to reduce file size, and users can choose whether to retain or strip metadata based on their needs. Stripping metadata can further shrink payloads and improve loading performance without affecting on-page rendering.

Performance and Quality

What does imgsquash recommend for best settings?

  1. Use AVIF or WebP for photos; prefer WebP lossless or PNG for flat graphics/logos, and always deliver responsive images (srcset/sizes) to avoid shipping oversized assets to mobile devices.
  2. Right-size images to container dimensions before compression; this avoids wasting bytes and directly improves LCP by reducing the largest element’s load time.
  3. Measure with field data: monitor LCP and other Web Vitals in Google Search Console’s Core Web Vitals report to validate improvements after format conversion and resizing rollouts.
  4. Maintain compatibility via the picture element with modern sources (AVIF/WebP) and JPEG/PNG fallbacks to ensure coverage across legacy clients while still achieving performance gains where supported.

Will compression reduce image quality?

ImgSquash provides fine-grained quality controls and next‑gen codecs to minimize visible artifacts while achieving substantial file-size reductions. AVIF/WebP often deliver smaller files at comparable perceived quality versus JPEG/PNG, improving speed without sacrificing UX.

Why use AVIF, WebP, or JPEG XL?

AVIF and WebP can dramatically lower image sizes, which improves LCP and crawl efficiency—both beneficial to search visibility and Core Web Vitals. For flat graphics or logos, WebP lossless or PNG may be more efficient than AVIF, so choosing by asset type yields the best outcomes.

Can I preview results before downloading?

ImgSquash’s workflow enables interactive tuning of output format and quality so users can preview and target desired visual fidelity and file size. Iterative previewing helps align performance goals with brand image standards and device-specific needs.

SEO and Experience Performance

How does ImgSquash help SEO?

Smaller images improve LCP and overall page speed, which can enhance rankings and engagement while enabling Google to crawl more pages efficiently. Adopting AVIF/WebP and right-sizing images contributes directly to better Core Web Vitals and user experience.

  • Largest Contentful Paint (LCP) is a Core Web Vitals metric that measures perceived loading speed for the largest element in the viewport, and Google advises keeping LCP within 2.5s for a good user experience.
  • Google confirms that page experience signals, including Core Web Vitals, are used in ranking systems, where better Web Vitals can serve as a tie-breaker among pages of similar quality.
  • Compressing and right-sizing images directly lowers bytes transferred, improving LCP and overall page speed, which can translate into higher rankings and better engagement as faster pages reduce bounce and increase user satisfaction.
  • Faster pages also improve crawl efficiency: Google’s documentation on managing crawl for large sites explains that quicker server responses can allow Googlebot to crawl more pages within the same time and bandwidth constraints, effectively increasing crawl throughput.

Will switching to AVIF/WebP break older browsers?

Use the picture element with AVIF/WebP sources and JPEG/PNG fallbacks to ensure compatibility across legacy clients while maximizing performance for modern browsers. Conditional delivery of next‑gen formats balances reach and speed without compromising rendering.

Troubleshooting

My output looks too compressed—what should I do?

Increase quality in small steps, try AVIF at slightly higher settings, or switch to WebP to change artifact characteristics while testing by template type. For logos/UI, use lossless WebP or PNG to preserve edges and flat colors.

Files are still large after conversion—why?

Photos generally compress best with AVIF/WebP lossy, while flat graphics compress best as WebP lossless or PNG, so match the format to the asset type. Large pixel dimensions inherently increase file size; consider resizing or using AI upscaling followed by compression for optimal quality-to-size ratios.

Bulk tasks slow down or stall—what can help?

9 times out of 10 this is a local resource limitation rather than the imgsquash service. Reduce batch size, close heavy tabs, and prefer devices with more RAM/CPU/GPU since everything runs locally. WebGPU acceleration can improve throughput on supported browsers and hardware.