Image Compressor
Reduce image file size locally with an adjustable quality setting.
How to compress an image
- 1
Choose an image
Select or drag and drop your image.
- 2
Adjust quality
Choose the balance between quality and file size.
- 3
Download
Download your converted image.
Reduce image file size without changing its pixel dimensions
Image Compressor is for reducing encoded file size while keeping the image width and height unchanged. A 2400 × 1600 photo remains 2400 × 1600 after compression; if the destination needs fewer pixels, Image Resizer is the separate operation.
SnakTool accepts one validated JPEG, PNG or WebP image and re-encodes it locally in the browser. For JPEG and WebP, the quality control changes the lossy encoding tradeoff. PNG follows its lossless browser encoding path, so moving the quality slider does not turn PNG into a lossy compressor.
The result reports the input bytes, output bytes and savings when compression meaningfully reduces the file. This makes the tool useful for web assets, email attachments and upload limits where byte size matters but the required pixel dimensions should stay intact.
Quality is an encoding setting, not a promised percentage reduction
The interface offers quality values from 10% to 95% for JPEG and WebP. A setting of 75% does not mean the output will be 75% of the original size, nor does it mean that exactly 25% of visual detail is removed. It is an encoder input that influences the tradeoff between compression and fidelity.
Two images with identical dimensions and the same quality setting can produce very different file sizes. A smooth photograph, a noisy night photo and a screenshot full of sharp text contain different visual information and compress differently.
Start from the visual requirement rather than a target savings claim. Try a reasonable quality, inspect important detail at the size people will actually see it, and lower quality only when the extra byte reduction is worth the additional artifacts.
JPEG compression is most useful when photographs can tolerate some loss
JPEG is already a lossy format, so compressing a JPEG means decoding its current pixels and encoding them again. Lower quality can reduce bytes by simplifying image information, but repeated lossy saves can accumulate blocking, ringing, smearing and loss of fine texture.
Photographs often tolerate this tradeoff better than interface screenshots, diagrams or text-heavy graphics. Pay special attention to hair, foliage, fabric, gradients, high-contrast edges and small lettering because these areas can reveal compression damage before the overall image looks obviously degraded.
Keep an original or higher-quality source when future editing matters. A smaller JPEG cannot later reconstruct detail discarded by an earlier lossy encoding.
WebP quality also trades size against fidelity
For a WebP source, SnakTool keeps WebP as the output format and passes the selected quality to the browser encoder. This can be useful when the destination already supports WebP and you want a smaller delivery copy without changing dimensions or switching formats.
Do not assume that every WebP will shrink substantially. A source may already have been encoded efficiently, and a second encode at a similar quality can save very little or can even be larger before SnakTool's fallback decision.
Compression also does not prove that the source WebP's original encoding mode has been preserved. The output is a browser re-encoding of the decoded still image, so retain the source when its original encoding characteristics matter.
PNG remains lossless and behaves differently from JPEG or WebP
PNG is commonly useful for screenshots, line art, interface graphics and images that need transparency. In SnakTool's compressor, PNG output remains PNG and uses lossless encoding; the JPEG/WebP quality control does not create a TinyPNG-style lossy color-quantization mode.
That distinction explains why a PNG may show little or no reduction. A specialized PNG optimizer can use techniques that are different from simply decoding and losslessly re-encoding pixels, while SnakTool deliberately does not claim those algorithms.
If a photographic PNG is unnecessarily large and the destination accepts a lossy format, format conversion may provide a larger reduction than lossless PNG compression. If transparency or exact decoded pixels matter, keep a transparency-capable lossless workflow instead of choosing a smaller format only for its byte count.
SnakTool keeps the original when re-encoding does not save enough
A compressor should not make you download a larger file just to say that processing succeeded. After re-encoding, SnakTool compares the candidate with the source. The candidate is used only when it saves more than the greater of 32 bytes or 1% of the original file size.
If that threshold is not exceeded, the tool returns the original bytes and reports that compression did not reduce the image meaningfully. This can happen with an already-efficient image, with a PNG that the browser cannot improve, or when the chosen lossy quality produces little benefit.
The fallback is important when interpreting the result: unchanged size does not mean the tool silently found a perfect new encoding. It means the original was the better file under the current meaningful-savings rule.
Compression does not guarantee a target size such as 100 KB
SnakTool does not repeatedly search quality levels until an exact target such as 500 KB, 200 KB or 100 KB is reached. You choose a quality for JPEG or WebP, the browser encodes once, and the resulting size depends on the image content and encoder.
If an upload form has a hard byte limit, compare the reported output size with that limit and adjust quality again when appropriate. If the file is still too large, reducing pixel dimensions with Image Resizer can remove far more image data than another small quality adjustment.
Treat dimensions and compression as separate controls. Resize when the destination does not need all the source pixels; compress when it needs the same dimensions but fewer encoded bytes. Combining the two deliberately is more predictable than expecting one quality number to solve every size limit.
Metadata behavior depends on whether the compressed candidate is kept
Normal compression is not SnakTool's dedicated metadata-removal workflow. When a newly encoded JPEG, PNG or WebP is accepted as smaller, it is produced from decoded pixels through the browser canvas rather than by copying the original file byte for byte.
However, when compression fails the meaningful-savings threshold, SnakTool deliberately returns the original bytes. Any metadata present in those original bytes is therefore retained in that fallback result.
Do not use file compression as a privacy guarantee. If EXIF, GPS, XMP, comments or text metadata are the concern, use Remove Image Metadata and verify that exported file separately. Visible identifying information inside the pixels is a different privacy issue again.
Transparency follows the source format rather than a format conversion
Image Compressor keeps the source format. PNG and WebP can therefore retain transparency through their supported browser encoding path, while JPEG remains an opaque format. The compressor does not offer a background-color control because it is not converting a transparent PNG or WebP into JPEG.
If you specifically need JPEG compatibility from a transparent source, use the corresponding format converter and choose the background that should replace transparent or semi-transparent pixels. That is a different decision from reducing the bytes of the current format.
Inspect translucent edges after any workflow that changes encoding. Alpha support tells you whether transparency can exist; it does not by itself guarantee that every color or edge will remain visually identical after a lossy encode.
Browser-local processing changes the data path and sets practical limits
SnakTool decodes and re-encodes the selected image locally in a browser worker using an offscreen canvas. The image does not need to be uploaded to a SnakTool compression backend, which is useful when you prefer a local processing path for the file.
The normal image policy accepts one image and bounds the job to 8192 pixels per side, 32 million pixels, 192 MiB of estimated memory, a 25 MiB output and 60 seconds of processing. Known low-memory devices use tighter ceilings, including 4096 pixels per side and 12 million pixels.
These limits protect the browser from unexpectedly expensive decoded images. Compressed input size alone is not a reliable measure of workload: a relatively small file can expand to many millions of RGBA pixels in memory.
Judge compression by the final use case, not file size alone
For a website, smaller image bytes can reduce transfer cost, but serving an image at appropriate dimensions and choosing a suitable format are separate optimization decisions. A huge 4000-pixel image does not become appropriately sized for a small card merely because its JPEG quality was lowered.
For email or form uploads, the hard requirement may simply be staying under a byte limit. For a portfolio, product image or screenshot, preserving detail may matter more than reaching the smallest possible file. The same compression setting should not be assumed to fit all of these cases.
Compare the downloaded image with the original around important edges, text, faces and texture. Then check the actual byte size and dimensions. A useful compressed image is the smallest version that still meets the visual and technical requirements of its destination.
What this tool supports
- Preserves image dimensions by default
- Supports adjustable JPEG and WebP quality
- Keeps PNG output lossless and transparent
Limitations
- Very large images are restricted to protect browser memory
- Lossy formats may change pixels slightly when re-encoded
Frequently asked questions about Image Compressor
How do I compress an image without changing its dimensions?
Choose one supported JPG, PNG or WebP image, select the quality when it applies, and run Image Compressor. SnakTool re-encodes the image at the same decoded width and height, so compression changes encoded bytes rather than intentionally resizing the pixel grid.
Which image formats can I compress?
The compressor accepts one validated JPEG, PNG or WebP still image. SnakTool inspects the actual file structure and dimensions instead of relying only on the filename extension.
What quality setting should I use for image compression?
There is no single best percentage for every image. Start with the visual requirement, inspect important details such as faces, text, gradients and edges, and lower quality only when the extra size reduction is worth the added artifacts.
Why is my PNG not getting much smaller?
PNG may already be efficiently encoded, and SnakTool does not use lossy PNG quantization or specialized optimization algorithms. A screenshot or graphic can therefore show little lossless reduction even when another service using a different PNG strategy produces a smaller file.
Can a compressed image become larger than the original?
The temporary re-encoded candidate can be larger, especially when the source was already efficient or the chosen quality is high. Image Compressor does not publish that candidate when it fails the meaningful-savings rule; it falls back to the original bytes.
Why do two images at the same dimensions and quality produce different file sizes?
Image content matters. Smooth areas, noise, texture, sharp text, gradients and fine detail have different encoding complexity, so equal dimensions and equal quality settings do not imply equal byte sizes.
Does compressing an image make it blurry?
It can at sufficiently aggressive JPEG or WebP quality settings. Lossy encoding can introduce softness, blocking, ringing or artifacts around fine detail and high-contrast edges. PNG remains on the lossless path in this compressor.
Does compressing a JPEG repeatedly reduce quality?
It can. Each accepted JPEG recompression starts from already decoded pixels and applies another lossy encode, so repeated generations can accumulate artifacts. Keep an original or high-quality source instead of using a repeatedly compressed copy as your editing master.
Does image compression preserve transparency?
The compressor keeps the source format. PNG and transparency-capable WebP can retain alpha through their supported encoding path, while JPEG remains opaque. Inspect translucent edges after lossy WebP encoding when exact appearance matters.
Why can a small image file still use a lot of memory while compressing?
Compressed file size is not decoded memory size. A large image can expand to roughly width times height times four bytes for its RGBA pixels, and the workflow also needs source and output resources, so a relatively small compressed file can still hit browser memory limits.
Why can image compression fail?
A malformed or unsupported image, invalid dimensions, a file the browser cannot decode or re-encode, or a job beyond the configured pixel, memory, output-size or processing-time limits can fail. The tool validates JPEG, PNG and WebP content rather than accepting an arbitrary file renamed with an image extension.
Choose between compression and resizing