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Image MIME Reference
JPEG-AI-Sequence

JPEG AI Image Sequence

image/jais
VS

Microsoft Document Imaging

image/vnd.ms-modi
MODI

A complete technical comparison of JPEG AI Image Sequence and Microsoft Document Imaging — covering compression, feature support, browser compatibility, magic bytes, and when to choose each format.

Equal browser support

Feature Support

Feature JPEG-AI-Sequence MODI
Transparency (Alpha) Yes ✕ No
Animation Support Yes ✕ No
Progressive Loading Yes ✕ No
HDR Support Yes ✕ No
EXIF Metadata Yes ✕ No
ICC Color Profile Yes ✕ No
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 →
Microsoft Document Imaging
image/vnd.ms-modi
Extension
.mdi
Container TIFF Variant
Compression LZW / Proprietary MS Compression
Algorithm
LZW (Modified)
Color Depth 1-bit (Monochrome), 8-bit (Grayscale), 24-bit (RGB)
Developed by Microsoft Corporation
Released 2001
Magic Bytes
49 49 2A 00
Full MODI reference →

Browser Support Comparison

Browser JPEG-AI-Sequence MODI
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
MODI

MODI Strengths

  • Historically provided an excellent all-in-one scanned document format with built-in OCR and annotations before PDF editing became universally accessible
  • Tightly integrated with Microsoft Office and SharePoint workflows in the early 2000s
Limitations
  • Completely proprietary and obsolete; Microsoft abandoned it in favor of standard TIFF and PDF
  • Causes widespread identification conflicts since its file signature is identical to a standard TIFF
  • Extremely difficult to open on modern operating systems without relying on third-party conversion utilities

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
MODI
Use MODI when…
  • Legacy Scanned Document Archival
  • Microsoft Office XP/2003/2007 Workflows
  • Embedded OCR Text Storage

More comparisons

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