Why AVIF Encoding Uses More Memory Than Decoding

AVIF (AV1 Image File Format) delivers superior compression efficiency compared to legacy formats like JPEG, but it exhibits a dramatic asymmetry in resource usage: encoding requires substantially more memory and processing power than decoding. While decoding simply executes a predefined set of instructions to reconstruct an image, encoding requires an exhaustive mathematical search through thousands of compression possibilities to determine the most efficient representation of that image. This article breaks down the technical reasons behind AVIF's high encoder memory footprint, including search-space evaluation, working memory buffers, multi-threading overhead, and the relative simplicity of the decoder pipeline.

The Search Space: Evaluation vs. Execution

The primary reason for the memory disparity is that encoders are decision-makers, whereas decoders are merely executors.

To achieve high compression ratios, an AV1 encoder must evaluate numerous ways to represent every block of pixels. It tests block partitions ranging from 4x4 to 128x128 pixels, dozens of intra-prediction directional modes, and multiple transform types (such as DCT, ADST, or identity transforms).

To select the best combination, encoders use Rate-Distortion Optimization (RDO). RDO requires the encoder to repeatedly encode, reconstruct, and calculate the visual error and bit cost of each candidate configuration. To perform these comparisons, the encoder must store the original pixel data, the predicted data, the residual data (differences), and multiple temporary reconstructed candidate blocks in RAM simultaneously. A decoder, by contrast, reads the specific mode already selected by the encoder and immediately generates the pixels, needing zero trial-and-error storage.

Working Buffers and Frame Duplication

During the encoding pipeline, several full or partial copies of the image must be kept in volatile memory at various stages of processing:

• Source Frame Buffer: The uncompressed original image data.
• Pre-filtered Buffer: An intermediate buffer used if noise reduction, scaling, or color-space conversion is applied prior to encoding.
• Reconstructed Frame Buffer: The encoder must build its own copy of what the decoder will see to calculate accurate residuals for neighboring blocks.
• Lookahead and Pre-analysis Buffers: Advanced encoders analyze spatial complexity and visual contrast across the image before assigning quantization parameters. Storing data for these lookahead passes requires substantial additional memory.

A decoder needs only a minimal scratchpad memory and a single destination buffer to store the final output pixels.

Multi-Threading and Memory Multiplication

Because AV1 encoding is computationally heavy, modern encoders (like libaom or rav1e) rely heavily on parallel processing to achieve acceptable speeds. They achieve this by splitting images into independent tiles or rows and processing them concurrently using multiple worker threads.

Each active thread requires its own independent memory allocation to store its local search state, transform coefficients, and block candidates. If an encoder runs 16 threads in parallel, the scratchpad and intermediate buffer memory is multiplied accordingly. Decoding can also be multithreaded, but the memory footprint of each decoder worker is negligible because it only allocates space for simple bitstream parsing and pixel rendering.

Decoders Are Built for Lightweight Execution

The AV1 specification was intentionally engineered to ensure decoding could run smoothly on low-power devices, such as smartphones, smart TVs, and embedded systems.

Decoders do not make choices; they simply read the bitstream syntax, look up entropy tables, perform inverse discrete cosine or directional transforms, and apply post-processing filters (such as the deblocking filter, Constrained Directional Enhancement Filter, and loop restoration). These filters operate in fixed, sliding-window pipelines that process pixel rows sequentially, requiring only a tiny fraction of the working memory consumed by the encoder's speculative search algorithms.