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Image MIME Reference
JPEG-AI-Sequence

JPEG AI Image Sequence

image/jais
VS

TIFF for Facsimile eXtended

image/tiff-fx
TIFF-FX

A complete technical comparison of JPEG AI Image Sequence and TIFF for Facsimile eXtended — covering compression, feature support, browser compatibility, magic bytes, and when to choose each format.

Equal browser support

Feature Support

Feature JPEG-AI-Sequence TIFF-FX
Transparency (Alpha) Yes ✕ No
Animation Support Yes ✕ No
Progressive Loading Yes ✕ No
HDR Support Yes ✕ No
EXIF Metadata Yes ✕ No
ICC Color Profile Yes Yes
JPEG AI Image Sequence
image/jais
Extension
.jais
Container ISOBMFF / HEIF Image Sequence
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 73 (Size + ftypjais)
Full JPEG-AI-Sequence reference →
TIFF for Facsimile eXtended
image/tiff-fx
Extension
.tiff.tif
Container TIFF 6.0 Tag Directory Structure
Compression MH / MR / MMR (CCITT Group 3 & 4) / JBIG / JPEG
Algorithm
CCITT Group 3/4JBIGJPEG
Color Depth 1-bit (Monochrome B&W), 8-bit (Grayscale/Color Indexed), 24-bit (RGB Color)
Developed by IETF (Internet Engineering Task Force)
Released 1998
Magic Bytes
49 49 2A 00 (Little-Endian) / 4D 4D 00 2A (Big-Endian)
Full TIFF-FX reference →

Browser Support Comparison

Browser JPEG-AI-Sequence TIFF-FX
Chrome Chrome
✕ ✕
Firefox Firefox
✕ ✕
Safari Safari
✕ ✕
Edge Edge
✕ ✕
IE IE (Legacy)
✕ ✕
JPEG-AI-Sequence

JPEG-AI-Sequence Strengths

  • Extends the state-of-the-art compression efficiency of JPEG AI to multi-frame image sequences and short animations
  • Allows machine vision algorithms to process temporal sequences (like surveillance bursts) directly in the compressed latent domain, saving immense computational power
  • Utilizes the robust, industry-standard ISOBMFF container for metadata, timing, and multi-track encapsulation
Limitations
  • Lacks native decoding support in current web browsers, operating systems, and video players
  • Decoding neural-network-compressed sequences requires significant compute overhead on hardware lacking dedicated AI accelerators (NPUs/GPUs)
  • Adoption is hindered by competition with established sequence formats like AVIF, HEVC (HEICS), and modern video codecs
TIFF-FX

TIFF-FX Strengths

  • Provides a universal, standardized format for transmitting multi-page documents over IP networks and email (Internet Fax)
  • Supports highly efficient telecom-centric compression algorithms (MMR, JBIG) that produce very small files for text documents
  • Maintains backwards compatibility with standard TIFF parsers
Limitations
  • Not supported natively by web browsers
  • Requires complex parsing of TIFF IFD tags to differentiate a true TIFF-FX file from a standard TIFF file
  • Usage is slowly declining as traditional faxing is replaced by secure PDF transmission and e-signature platforms

When to choose which format

JPEG-AI-Sequence
Use JPEG-AI-Sequence when…
  • Machine Vision and AI Video/Burst Workflows
  • Cloud Storage Animation Optimization
  • Focal Stacks and Medical Volumetric Slices
  • Visual Surveillance Sequences
TIFF-FX
Use TIFF-FX when…
  • Internet Fax (T.37)
  • Enterprise Fax Servers
  • Document Archiving
  • Telecommunications

More comparisons

JPEG-AI-Sequence vs ACES → TIFF-FX vs ACES → JPEG-AI-Sequence vs APNG → TIFF-FX vs APNG → JPEG-AI-Sequence vs AVCI → TIFF-FX vs AVCI → JPEG-AI-Sequence vs AVCS → TIFF-FX vs AVCS → JPEG-AI-Sequence vs AVIF → TIFF-FX vs AVIF → All comparisons →
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