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Image MIME Reference
JPEG-AI-Sequence

JPEG AI Image Sequence

image/jais
VS

Portable Graymap

image/x-portable-graymap
PGM

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

Equal browser support

Feature Support

Feature JPEG-AI-Sequence PGM
Transparency (Alpha) Yes ✕ No
Animation Support Yes ✕ No
Progressive Loading Yes ✕ No
HDR Support Yes Yes
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 →
Portable Graymap
image/x-portable-graymap
Extension
.pgm
Container Netpbm
Compression Uncompressed
Algorithm
None
Color Depth 8-bit (Grayscale), 16-bit (Grayscale)
Developed by Jef Poskanzer (Netpbm Project)
Released 1988
Magic Bytes
50 32 (ASCII) or 50 35 (Binary)
Full PGM reference →

Browser Support Comparison

Browser JPEG-AI-Sequence PGM
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
PGM

PGM Strengths

  • Extremely simple format allows custom parsers to be written from scratch in minimal time
  • Supports 16-bit precision, making it highly valuable for scientific, medical, and height-map data where 8-bit precision is insufficient
  • ASCII encoding ('P2') allows manual editing and visual inspection of pixel values directly within a text editor
Limitations
  • Strictly limited to grayscale; cannot display color
  • Lack of compression results in massive file sizes, making it entirely impractical for web delivery or consumer storage
  • Does not support alpha transparency or modern metadata structures

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
PGM
Use PGM when…
  • Computer Vision and Machine Learning Pre-processing
  • Scientific and Medical Image Processing
  • Unix/Linux Command-Line Image Pipelines

More comparisons

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