How AVIF Achieves Smaller File Sizes Than JPEG

The AV1 Image File Format (AVIF) significantly outperforms legacy JPEG by leveraging modern compression algorithms originally developed for next-generation video streaming. By adopting the AV1 video codec's intra-frame encoding capabilities, AVIF dramatically reduces image file sizes—often by 50% or more compared to JPEG—while preserving superior visual detail, dynamic range, and color fidelity.

Roots in the AV1 Video Codec

JPEG relies on compression standards established in 1992, designed during an era of extreme computational constraints. In contrast, AVIF is an image format derived from the AV1 video standard, developed by the Alliance for Open Media (AOMedia). Modern video codecs require immense compression efficiency to stream 4K and 8K content over constrained network bandwidths. AVIF applies these advanced video intra-frame (keyframe) compression techniques directly to still images, instantly leapfrogging decades of legacy limitations.

Dynamic Block Partitioning

Legacy JPEG splits an image into rigid, non-negotiable grids of 8x8 pixel blocks, applying compression uniformly across the entire canvas regardless of image complexity.

AVIF replaces this rigid grid with flexible "superblocks" that range from 4x4 up to 128x128 pixels. Smooth, low-detail areas like skies or clean backgrounds are grouped into large blocks and encoded with minimal data. Complex, detailed areas like text, hair, or textures are recursively divided into smaller blocks to retain edge precision. This variable partitioning eliminates wasted data in simple regions without sacrificing sharpness where it matters most.

Advanced Intra-Frame Prediction

Instead of encoding every pixel from scratch, AVIF analyzes surrounding pixels to predict what the current block should look like. It features dozens of directional prediction modes, allowing the encoder to extrapolate textures, gradients, and angles across neighboring blocks. The file only needs to store the mathematical difference (residual data) between the prediction and the actual image, significantly reducing the amount of data written to disk.

Modern Entropy Coding

Once pixel data is predicted and transformed, it must be converted into a stream of binary bits. While JPEG relies on older Huffman coding or basic arithmetic coding, AVIF uses sophisticated modern entropy coding based on multi-symbol arithmetic coding. This mathematical process packs the final bitstream far more efficiently, eliminating statistical redundancies in the data.

Integrated In-Loop Filtering

High compression in JPEG causes harsh "blockiness" and color banding because boundaries between 8x8 blocks become visible. To combat this, JPEG requires higher bitrates to maintain quality.

AVIF incorporates hardware-accelerated in-loop filters, including:

• Deblocking filters: Smooth unnatural seams across block boundaries.
• Constrained Directional Enhancement Filter (CDEF): Identifies directional edges and sharpens them while suppressing ringing artifacts.
• Loop Restoration filters: Fine-tune overall image textures and reduce noise.

These filters run during the decoding process, allowing the encoder to compress data more aggressively while the decoder reconstructs a clean, artifact-free image.

Higher Bit Depth and Efficient Color Handling

JPEG is fundamentally limited to 8-bit color depth, meaning it only has 256 levels per color channel. This frequently leads to visible banding in gradients, forcing encoders to use lower compression ratios to hide imperfections. AVIF natively supports 10-bit and 12-bit color depths (1,024 and 4,096 levels per channel). Higher bit depth not only enables High Dynamic Range (HDR) and wider color gamuts (such as DCI-P3 and BT.2020), but it also allows the compression algorithms to represent subtle gradients cleanly at a fraction of the file size.