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MiniPx vs MozJPEG

MiniPx

minipx.com

MozJPEG

github.com

Side by side

FigureMiniPxMozJPEG
Price fromFreeFree
Free planYesYes
Free trialYes—
Open source——
WebYes—
Windows—Yes
macOS—Yes
Linux—Yes
API—Yes
Self-hosted—Yes
Plans published31
Spec score · Image Compression Software8.8 (#8)8.2 (#32)
API accessNoYes
Compression modesbothboth
Free planYesYes
Metadata controlsYesYes
Supported formatsJPEG,PNG,WebP,AVIF,HEIC,BMP,SVG,GIF,TIFFPPM,PGM,BMP,GIF,Targa

Plans

MiniPx

  • FreeFree
  • Pro MonthlyPrice not published
  • Pro Annual$2,939 a year

MiniPx pricing →

MozJPEG

  • MozJPEGFree

MozJPEG pricing →

In their own words

MiniPx

MiniPx is a browser-based tool for compressing, converting, and resizing images, with additional tools for background removal, upscaling, and passport photo creation. Its free plan keeps compression, conversion, and resizing unlimited without signup or a daily cap. It accepts JPEG, PNG, WebP, AVIF, HEIC, BMP, SVG, GIF, and TIFF files; free batches are limited to five files. Compression presets are Gentle, Smart, and Tiny, and users can set a target size from 10 KB through 1 MB. Compression, conversion, and resizing run locally in the browser without uploading image files, and outputs remove EXIF metadata such as location and device information. Those core tools work offline after the first page load. Three on-device AI tools share two free runs before a cooldown, and need model downloads on first use. Pro adds unlimited batch processing, text watermarking, presets, responsive exports, and an opt-in cloud path for seven AI tools. The free plan costs nothing. Pro Annual costs $2,939 a year; no monthly Pro price is listed.

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MozJPEG

MozJPEG is a free, open-source library project that improves JPEG compression efficiency to produce smaller files and higher visual quality. It is intended for graphics programs and image-processing tools, and programs using the libjpeg API can integrate it without MozJPEG-specific integration code. It is compatible with the JPEG standard and the vast majority of deployed JPEG decoders. When converting other formats to JPEG, it uses trellis quantization to target the quality-to-file-size ratio. Its progressive encoding with jpegrescan optimization can losslessly reduce the size of a JPEG when used with jpegtran. The project’s improvements can be disabled at runtime, returning it to libjpeg-turbo behavior. The repository includes a demo cjpeg command-line tool, which is not intended for serious use. Build instructions cover Unix-like systems, macOS, Linux, and Windows with Visual C++ or MinGW. The GitHub repository identifies version 4.1.1 on its latest release page. MozJPEG points users to libjpeg-turbo documentation for additional build help; its repository does not state security certifications or compliance claims.

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