Image MIME Reference
IEF
Image Exchange Format
image/ief
VS
JPEG AI Image
image/jaii
JPEG-AI
A complete technical comparison of Image Exchange Format and JPEG AI Image — covering compression, feature support, browser compatibility, magic bytes, and when to choose each format.
Equal browser support
Feature Support
| Feature | IEF | JPEG-AI |
|---|---|---|
| Transparency (Alpha) | ✕ No | Yes |
| Animation Support | ✕ No | Yes |
| Progressive Loading | ✕ No | Yes |
| HDR Support | ✕ No | Yes |
| EXIF Metadata | ✕ No | Yes |
| ICC Color Profile | ✕ No | Yes |
Image Exchange Format
image/ief
Extension
.ief
Container
TIFF Class B (TIFF-B)
Compression
Lossless (MH, MR, MMR) / Uncompressed
Algorithm
MHMRMMRUncompressed
Color Depth
1-bit (Monochrome)
Developed by
IETF Network Fax Working Group
Released
1992
Magic Bytes
49 49 2A 00 (Little-endian) / 4D 4D 00 2A (Big-endian)
JPEG AI Image
image/jaii
Extension
.jaii
Container
ISOBMFF / HEIF
Compression
Lossy (Variational Autoencoder / Neural Network)
Algorithm
Deep Neural Network (Variational Autoencoder with Hyperpriors)
Color Depth
8-bit, 10-bit, 12-bit, 16-bit, Wide-gamut & HDR
Developed by
Joint Photographic Experts Group (ISO/IEC JTC 1 / ITU-T)
Released
2025
Magic Bytes
.. .. .. .. 66 74 79 70 6A 61 69 69 (Size + ftypjaii)
Browser Support Comparison
| Browser | IEF | JPEG-AI |
|---|---|---|
Chrome
|
✕ | ✕ |
Firefox
|
✕ | ✕ |
Safari
|
✕ | ✕ |
Edge
|
✕ | ✕ |
IE (Legacy)
|
✕ | ✕ |
IEF
IEF Strengths
- Provided a standard method for exchanging bi-level fax images during the early days of the Internet
- Supported multi-page documents
- Leveraged the highly resilient and well-documented TIFF container
Limitations
- Completely obsolete and unsupported in modern computing environments
- Strictly limited to 1-bit monochrome data, lacking color or grayscale capabilities
- Magic bytes overlap completely with standard TIFF, making specific filetype detection difficult without parsing internal tags
JPEG-AI
JPEG-AI Strengths
- Provides state-of-the-art compression efficiency, dramatically outperforming traditional block-transform codecs like JPEG or HEIC [2.2.2]
- Allows machine vision models to process the raw 'latent tensors' in the compressed stream natively, drastically reducing inference latency by bypassing image reconstruction
- Supports 'multi-branch decoding', enabling a single codestream to be decoded at varying complexity levels depending on the target hardware's power (e.g., mobile NPU vs. cloud GPU)
Limitations
- Lacks native decoding support in current web browsers and legacy operating systems [3.2.1]
- Decoding relies on neural network inference which can be heavily computationally demanding on hardware lacking dedicated AI accelerators (NPUs/GPUs)
- Introduces new vectors for security and forensic analysis, as end-to-end learned structures react differently to adversarial attacks compared to traditional formats
When to choose which format
IEF
Use IEF when…
- Legacy Fax Transmissions
- Early Internet Gateways
- Archival
JPEG-AI
Use JPEG-AI when…
- Machine Vision and AI Workflows
- Cloud Storage Image Optimization
- High-Efficiency Mobile Image Capture
- Visual Surveillance