Optimize images without quality loss
🤖/image/optimize reduces the size of images while maintaining the same visual quality.

🤖/image/optimize reduces the size of images while maintaining the same visual quality.

With this Robot it's possible to reduce the file size of your JPEG, PNG, GIF, WEBP and SVG images by up to 80% for big images and 65% for small to medium sized ones — while keeping their original quality!
This Robot enables you to lower your storage and bandwidth costs, and improves your user experience and monetization by reducing the load time of image-intensive web pages.
It works well together with 🤖/image/resize to bring the full power of resized and optimized images to your website or app.
This Robot accepts all image types and will just pass on unsupported image types unoptimized, including JPEG XL (.jxl) images when no smaller optimized result can be produced. Hence, there is no need to set up 🤖/file/filter workflows for this.
PNG optimization uses only lossless (optipng) compressors by default. To also enable lossy compression (pngquant), set lossy: true. When enabled, both lossy and lossless compressors compete and the smallest result wins, which may cause color shifts in some images.
Optimize uploaded images:
{
"steps": {
"optimized": {
"robot": "/image/optimize",
"use": ":original"
}
}
}interpolateboolean | Record<string, boolean>Controls whether Assembly Variables are interpolated for individual instruction fields.
By default, most Robot instruction fields interpolate Assembly Variables. Set this to false to treat every instruction field as literal text, or set an individual field path to false to treat only that field as literal text. For Robot-specific fields that are literal by default, set this to true or set that field path to true to opt back into interpolation.
Use field names such as path, or dotted paths such as ffmpeg.vf for nested objects.
output_metaRecord<string, boolean> | boolean | Array<string>Allows you to specify a set of metadata that is more expensive on CPU power to calculate, and thus is disabled by default to keep your Assemblies processing fast.
For images, you can add "has_transparency": true in this object to extract if the image contains transparent parts and "dominant_colors": true to extract an array of hexadecimal color codes from the image.
For images, you can also add "blurhash": true to extract a BlurHash string — a compact representation of a placeholder for the image, useful for showing a blurred preview while the full image loads.
For videos, you can add the "colorspace: true" parameter to extract the colorspace of the output video.
For videos, you can also add "interlaced": true to detect whether the video is interlaced. This combines the cheap ffprobe field_order flag with a bounded idet sampling pass over the first frames of the source, exposing interlaced, field_order, and a diagnostic interlace_detection object under file.meta. This is computationally expensive and billed accordingly.
For audio, you can add "mean_volume": true to get a single value representing the mean average volume of the audio file.
You can also set this to false to skip metadata extraction and speed up transcoding.
resultboolean (default: false)Whether the results of this Step should be present in the Assembly Status JSON
queuebatchSetting the queue to 'batch', manually downgrades the priority of jobs for this step to avoid consuming Priority job slots for jobs that don't need zero queue waiting times
force_acceptboolean (default: false)Force a Robot to accept a file type it would have ignored.
By default, Robots ignore files they are not familiar with. 🤖/video/encode, for example, will happily ignore input images.
With the force_accept parameter set to true, you can force Robots to accept all files thrown at them.
This will typically lead to errors and should only be used for debugging or combatting edge cases.
ignore_errorsboolean | Array<meta | execute> (default: [])Ignore errors during specific phases of processing.
Setting this to ["meta"] will cause the Robot to ignore errors during metadata extraction.
Setting this to ["execute"] will cause the Robot to ignore errors during the main execution phase.
Setting this to true is equivalent to ["meta", "execute"] and will ignore errors in both phases.
usestring | Array<string> | Array<object> | objectSpecifies which Step(s) to use as input.
":original" (reserved for user uploads handled by Transloadit){
"use": [
":original",
"encoded",
"resized"
]
}
as to pass semantic intent to robots:as to pass semantic intent to robots:
{
"use": [
{
"name": ":original",
"as": "image"
},
{
"name": ":original",
"as": "mask"
}
]
}
That's likely all you need to know about use, but you can view Advanced use cases.
prioritycompression-ratio | conversion-speed (default: "conversion-speed")Provides different algorithms for better or worse compression for your images, but that run slower or faster. The value "conversion-speed" will result in an average compression ratio of 18%. "compression-ratio" will result in an average compression ratio of 31%.
progressiveboolean (default: false)Interlaces the image if set to true, which makes the result image load progressively in browsers. Instead of rendering the image from top to bottom, the browser will first show a low-res blurry version of the image which is then quickly replaced with the actual image as the data arrives. This greatly increases the user experience, but comes at a loss of about 10% of the file size reduction.
preserve_meta_databoolean (default: true)Specifies if the image's metadata should be preserved during the optimization, or not. If it is not preserved, the file size is even further reduced. But be aware that this could strip a photographer's copyright information, which for obvious reasons can be frowned upon.
fix_breaking_imagesboolean (default: true)If set to true this parameter tries to fix images that would otherwise make the underlying tool error out and thereby break your Assemblies. This can sometimes result in a larger file size, though.
lossyboolean (default: false)When set to false (the default), only lossless PNG optimizers are used, disabling pngquant to preserve color accuracy.
When set to true, both lossy and lossless PNG optimizers compete and the smallest result wins. This allows pngquant, a lossy compressor that reduces PNGs to a 256-color palette, which may cause noticeable color shifts in images with rich color palettes, subtle gradients, or brand-specific colors.
This parameter only affects PNG optimization. JPEG, GIF, WebP, and SVG optimization is unaffected.