Convert PNG to AVIF
Compress PNG images into the efficient AVIF format, processed locally in your browser.
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How to use PNG to AVIF converter?
Upload your PNG files
Drag and drop your PNG images onto the drop zone, or click Select Files to browse. For png to avif bulk conversion, click Select Folder to load an entire directory of PNG files at once — all files are queued instantly with no upload needed.
Convert PNG to AVIF
Hit the Convert button and the png to avif conversion runs instantly in your browser via WebAssembly — fast, completely private, and no internet connection needed after the page loads.
Download your AVIF files
Once the png to avif conversion is done, download each AVIF file individually, or use Download All / Download ZIP to save everything in one click.
Why use our PNG to AVIF converter?
100% Local Processing
Your PNG files never leave your device. This png to avif converter runs entirely in your browser — no uploads, no servers, no privacy risk whatsoever.
Bulk PNG to AVIF Conversion
Convert entire folders of PNG images to AVIF in one go. The png to avif bulk mode lets you select hundreds of files at once and process them all simultaneously — no server queues, no waiting.
Dramatically Smaller File Sizes
AVIF achieves 50–70% smaller file sizes than PNG at comparable visual quality. Convert your PNGs to AVIF and cut storage costs, bandwidth usage, and page load times in one step.
Transparency Fully Preserved
PNG's alpha channel carries over perfectly during png to avif conversion. Transparent backgrounds, logos, and cutouts remain pixel-accurate in the output AVIF file.
Adjustable Output Quality
Fine-tune AVIF output quality before converting. Choose lossless for perfect fidelity or dial down the quality setting for maximum compression — the choice is yours.
Flexible Download Options
After the png to avif conversion, download files individually, all at once, or as a single ZIP archive — whichever fits your workflow best.
Why convert PNG to AVIF?
50–70% smaller files after PNG to AVIF conversion
PNG is lossless but expensive in storage. A typical PNG photograph or detailed graphic can be 3–5× the size of an equivalent AVIF file. Using a png to avif converter reduces that overhead dramatically — often 50–70% — without any visible quality loss when using lossless AVIF encoding. Smaller files mean faster page loads, lower CDN costs, and better Core Web Vitals scores.
Transparency support with far better compression
PNG became the default for transparent images because JPG doesn't support alpha channels. AVIF does — and it handles transparency at a fraction of the file size. When you convert PNG to AVIF, icons, logos, product cutouts, and UI graphics retain their transparent backgrounds while shrinking significantly. All the benefits of PNG's alpha channel, without the bloated file sizes.
Bulk convert entire PNG libraries in one session
If you have hundreds of PNG assets — screenshots, exports, design files — converting them one at a time is impractical. The png to avif bulk feature lets you select an entire folder and process everything simultaneously, right in your browser. No upload queue, no server wait, no file limit. It's the fastest way to migrate a large PNG library to AVIF.
Lossless AVIF: same quality, smaller size
Unlike converting PNG to JPG — which always discards pixel data — converting PNG to AVIF in lossless mode preserves every pixel exactly. You get the same bit-perfect quality as the original PNG, stored in a format that compresses more efficiently. Identical fidelity, smaller footprint, ready for modern browsers.
Future-proof format with broad modern browser support
AVIF is supported by Chrome, Firefox, Safari, and Edge — covering over 95% of global browser traffic. It's not an emerging experiment; it's the current standard for next-generation image delivery. Converting your PNG assets to AVIF today positions your site for performance and compatibility well into the future.
About PNG and AVIF file
PNG
Portable Network Graphics
PNG was originally expanded as "PNG's Not GIF," and the name itself tells you that it has a lot to do with GIF. Before PNG appeared, GIF was the undisputed king of web images. Then, in the early 1990s, Unisys, the company that held the rights to GIF, suddenly announced that it would charge patent fees to all software developers whose products supported GIF. To break that commercial monopoly, developers created a new image format that was completely open, free from commercial control, and technically better than GIF: PNG. So why was PNG technically better than GIF? It used a two-step compression algorithm. The first step was predictive filtering, which is the real core of PNG compression. Instead of recording the original value of each pixel, it records the difference between the current pixel and nearby pixels. This means the image data ends up being stored as lots of small, similar values, which greatly improves compression efficiency. The second step was Deflate compression, which combines the LZ77 algorithm with Huffman coding, a highly stable compression method that has been thoroughly tested over time. PNG uses lossless compression, which means it preserves all pixel data for high fidelity, and it also supports an alpha channel, so it can store transparency information as well.
AVIF
AV1 Image File Format
When talking about AVIF, you really have to start with AOMedia, the Alliance for Open Media, whose members include giants like Google, Netflix, Amazon, Microsoft, and Apple. In a way, AVIF was born for a reason very similar to PNG: it was created to break the patent monopoly of the HEIC format. Technically, AVIF also solved some of the quality problems WebP can run into at very high compression levels, especially visible blockiness, while significantly improving compression efficiency at the same time. If you want to make your web pages load faster and reduce image size, using AVIF is a very smart choice. So why is AVIF so efficient? One major reason is its intra-prediction algorithm. With very little data, it can still model complex textures, almost like a sketch artist analyzing the direction of lines in an image before drawing them in.