The Future of Image Formats: What Comes After HEIC

The next decade of image formats will be defined by royalty-free codecs, AI-driven compression, and the slow decline of JPEG. HEIC proved that modern codecs could halve file sizes compared to JPEG. Multiple successors now compete to inherit that efficiency without the patent baggage that limited HEIC's reach.

This guide maps out the formats vying to shape the future. For background on today's standard, see What Is HEIC?.

The Current Landscape in 2026

Three format tiers define the image ecosystem today. JPEG remains the universal baseline. HEIC dominates Apple device storage. WebP and AVIF are winning the web.

| Format | Primary Use | Global Adoption | Licensing | | --- | --- | --- | --- | | JPEG | Universal fallback | 100% browser support | Royalty-free (patents expired) | | PNG | Lossless, transparency | 100% browser support | Royalty-free | | WebP | Web delivery | 97%+ browser support | Royalty-free (Google) | | HEIC | Apple device capture | ~30-35% browser support | Patent royalties (HEVC) | | AVIF | Next-gen web delivery | 93%+ browser support | Royalty-free (AOMedia) | | JPEG XL | Professional imaging | Safari only, no Chrome | Royalty-free |

JPEG accounts for roughly 73% of all images served on the web. WebP has grown to approximately 15%. AVIF sits near 5% and climbing. HEIC web usage remains below 1% due to browser limitations documented in HEIC Browser Support. Apple ships over 1.2 billion active devices that default to HEIC capture, ensuring the format remains relevant regardless of web trends.

AVIF: The Leading Successor for the Web

AVIF is the most likely format to dominate web image delivery by 2030. It combines royalty-free licensing, strong compression, and backing from every major tech company.

Technical foundations

AVIF uses the AV1 codec developed by the Alliance for Open Media. AOMedia's 48 members include Google, Apple, Microsoft, Mozilla, Netflix, Amazon, and Meta. AV1 delivers 30-50% smaller files than JPEG at equivalent visual quality. For detailed benchmarks, see HEIC vs AVIF.

Browser adoption trajectory

AVIF browser support has followed a rapid adoption curve:

| Year | Milestone | Cumulative Browser Support | | --- | --- | --- | | 2020 | Chrome 85, Edge 85 launch AVIF support | ~65% | | 2021 | Firefox 93 adds AVIF | ~68% | | 2022 | Samsung Internet 16 adds support | ~72% | | 2023 | Safari 16.4 adds AVIF support | ~91% | | 2024 | Safari 17 adds animated AVIF | ~93% | | 2026 | All major browsers support AVIF | ~93%+ |

The remaining 7% without AVIF support consists of outdated browser versions. That gap shrinks each month as users update.

Remaining limitations

AVIF encoding is slow. A single 12 MP image takes 1-5 seconds with software encoders. Hardware AV1 encoders in Intel Arc, NVIDIA RTX 40-series, and AMD RDNA 3 GPUs are closing this gap. Mobile AV1 hardware encoding remains rare, preventing AVIF from replacing HEIC for real-time camera capture.

JPEG XL: The Best Format Nobody Can Use

JPEG XL is technically superior to every other image format but lacks the browser support to matter. It offers lossless JPEG recompression, progressive decoding, and compression that matches or beats AVIF -- all royalty-free.

What makes JPEG XL exceptional

JPEG XL (JXL) was standardized by the Joint Photographic Experts Group in 2022. Its standout capabilities include:

• Lossless JPEG recompression: converts existing JPEG files 20% smaller with zero quality loss
• Progressive decoding: images render at low quality first, then sharpen as data arrives
• Up to 32-bit color depth: exceeds both HEIC (16-bit) and AVIF (12-bit)
• Fast encoding and decoding: 3-10x faster than AVIF encoding

The Chrome decision that changed everything

Google removed JPEG XL support from Chrome in October 2023. The stated reason was insufficient ecosystem interest. This decision killed JPEG XL's web viability because Chrome holds 65% of browser market share. Safari added support in Safari 17 (September 2023). Firefox never added support. The result is a format that works in roughly 18% of browsers.

Where JPEG XL survives

JPEG XL has found adoption in professional workflows. Adobe Camera Raw supports JXL export. The darktable photo editor reads and writes JXL. Scientific imaging tools use JXL for its extreme resolution support. Image archivists value its lossless JPEG recompression for preserving legacy photo libraries.

JPEG XL's future depends on whether Chrome reverses its decision. Without Chrome, the format cannot reach critical mass for web delivery.

VVC: The Next-Generation Codec

Versatile Video Coding (VVC/H.266) delivers 40% better compression than HEVC and could power the next version of HEIC. VVC was standardized in July 2020 by the Joint Video Experts Team, the same group behind HEVC.

How VVC relates to image formats

The HEIF container format is codec-agnostic. HEIC is HEIF with HEVC encoding. AVIF is HEIF with AV1 encoding. A HEIF container with VVC encoding would create a format roughly 40% more efficient than current HEIC files.

The MPEG group published the VVC-based still image specification (VVIC) in 2022. No camera manufacturer or operating system has adopted it yet.

VVC adoption timeline

| Year | VVC Milestone | | --- | --- | | 2020 | VVC standard finalized (H.266/ISO 23090-3) | | 2021 | First hardware decoder prototypes demonstrated | | 2022 | VVIC still image specification published | | 2023 | Qualcomm Snapdragon 8 Gen 3 includes VVC hardware decode | | 2024 | MediaTek Dimensity 9400 adds VVC support | | 2025 | Apple A19 chip rumored to include VVC decode | | 2027-2030 | Projected timeframe for VVC-based image format adoption |

The patent problem repeats

VVC inherits the same patent licensing complexity that constrained HEIC. Multiple patent pools and individual holders create uncertainty. VVC-based image formats will not gain browser support from Mozilla or the open-source community. VVC's future in imaging mirrors HEIC's trajectory: hardware manufacturer adoption, open-source browser exclusion, limited web deployment.

Neural Image Compression: The AI Frontier

Learned image compression uses neural networks instead of hand-designed algorithms to encode images. Research models from Google, Meta, and academic labs achieve 30-50% better compression than HEVC at equivalent quality levels.

How neural compression works

Traditional codecs use fixed mathematical transforms to compress pixel data. Neural compression replaces these transforms with trained neural networks. An encoder network maps an image to a compact latent representation. A decoder network reconstructs the image from that representation. Both networks are jointly optimized to minimize file size while maximizing perceptual quality.

Current performance benchmarks

Research results from 2024-2025 demonstrate significant gains:

• Google's neural codec: 35% smaller than HEVC at SSIM parity on the Kodak test set
• Meta's DCVC-FM: 45% smaller than HEVC for natural photographs
• NVIDIA's learned compression: 30% reduction versus VTM (VVC reference encoder) on specific test images

Why neural compression is not ready

Three barriers prevent neural compression from replacing traditional codecs.

1. Decode speed: Neural decoders require GPU acceleration and still run 10-100x slower than hardware HEVC or AV1 decoders. A smartphone decoding a neural-compressed image takes 200-500 milliseconds versus 5-20 milliseconds for HEIC.
2. Hardware support: No shipping consumer device includes dedicated neural codec hardware. Traditional codecs benefit from billions of deployed hardware decoders.
3. Standardization: No international standards body has ratified a neural image compression standard. Without standardization, interoperability between encoders and decoders is not guaranteed.

Realistic deployment timeline for neural codecs is 2030-2035. Both dedicated hardware decoders and formal standardization must arrive first.

Computational Photography Changes Format Requirements

Modern smartphone cameras produce images that are composites of 9-30 exposures fused by AI. Apple iPhones, Google Pixels, and Samsung Galaxy devices all use multi-frame neural processing pipelines.

These pipelines generate data that legacy formats cannot efficiently represent:

• Depth maps: 3D scene information for portrait mode effects
• Segmentation masks: per-pixel labels identifying subjects, sky, foliage
• HDR gain maps: instructions for rendering on SDR and HDR displays
• Semantic metadata: AI-generated scene descriptions and object tags

HEIC already stores depth maps and gain maps in its multi-image container. Future formats will need to store even richer computational data efficiently.

Format Fragmentation Versus Consolidation

The image format landscape is fragmenting in the short term and will consolidate by 2030. The fragmentation phase is driven by competing codecs with different licensing models and ecosystem backing.

Current fragmentation

In 2026, a web developer must consider at least 4 formats: JPEG as fallback, WebP as baseline modern, AVIF for maximum compression, and HEIC for Apple upload workflows. For a comprehensive comparison, see HEIC vs WebP and Image Format Comparison.

Consolidation prediction

By 2030, the web will standardize on 2 formats: AVIF as the primary format and JPEG as the legacy fallback. WebP will be absorbed by AVIF as browser support reaches parity. JPEG XL will remain niche without Chrome support. VVC-based formats will serve hardware ecosystems but not the web. The pattern mirrors video: H.264 dominated for a decade, then royalty-free AV1 emerged as its successor.

Device capture remains separate

Camera capture formats and web delivery formats will remain distinct. Apple devices will continue capturing HEIC because hardware encoding efficiency matters for battery life. Web delivery will use AVIF because royalty-free licensing and universal browser support matter for distribution. This split means format conversion tools remain essential infrastructure.

Why HEIC Still Matters

HEIC is not going away. Dismissing it as a transitional format ignores the scale of Apple's ecosystem.

Installed base

Over 2.2 billion Apple devices have been sold since HEIC became the default in 2017. Every iPhone photo, iPad screenshot, and Mac screen capture produces HEIC files. These billions of existing HEIC files will need to be opened, shared, and converted for decades.

Apple's commitment

Apple has shown no indication of abandoning HEIC. iOS 18 and macOS 15 continue defaulting to HEIC capture. Apple's custom silicon includes dedicated HEVC hardware optimized for HEIC. Switching formats would require new hardware codec blocks and a migration path for existing photo libraries.

Transition timeline

HEIC will remain the dominant Apple capture format through at least 2030. Any transition to VVC would follow the same multi-year rollout as the JPEG-to-HEIC shift.

During this extended transition, converting HEIC to universally compatible formats remains a daily need for millions of users. HEICify handles this conversion directly in your browser -- no uploads, no installs, no waiting. The HEIC to JPG converter processes photographs while the HEIC to PNG converter preserves lossless quality and transparency.

Timeline of Image Format Evolution

| Year | Format | Event | | --- | --- | --- | | 1992 | JPEG | Standard published | | 1996 | PNG | Released as patent-free GIF alternative | | 2010 | WebP | Google releases WebP based on VP8 | | 2013 | HEVC | H.265 finalized, enabling HEIC | | 2017 | HEIC | Apple adopts HEIC as default (iOS 11) | | 2018 | AV1 | AOMedia releases royalty-free AV1 codec | | 2019 | AVIF | AVIF specification finalized | | 2020 | VVC | H.266 finalized with 40% gain over HEVC | | 2020 | AVIF | Chrome 85 ships AVIF support | | 2022 | JPEG XL | ISO standard finalized | | 2023 | JPEG XL | Chrome removes JPEG XL support | | 2023 | AVIF | Safari 16.4 completes major browser adoption | | 2025-2030 | Neural | Projected first commercial neural codecs | | 2027-2030 | VVC images | Projected VVC-based image format adoption |

What This Means for You Today

The format transition is happening now, and conversion tools bridge the gap. You do not need to wait for the future to arrive. The practical steps are clear.

1. Keep HEIC originals from Apple devices for maximum quality archival storage.
2. Convert to JPEG or PNG when sharing with anyone outside the Apple ecosystem.
3. Use AVIF or WebP for web publishing to get modern compression with broad support.
4. Ignore JPEG XL for web delivery until Chrome adds support.
5. Monitor VVC and neural compression as long-term developments, not immediate concerns.

HEICify exists precisely for step 2 -- converting HEIC files instantly in your browser during this era of format transition. All processing runs client-side using Web Workers, so your photos never leave your device. As formats evolve, the need to convert between incompatible ecosystems will persist for years to come.