Image MIME Reference
JPEG-AI
JPEG AI Image
image/jaii
VS
Portable Graymap
image/x-portable-graymap
PGM
A complete technical comparison of JPEG AI Image 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 | 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
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)
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)
Browser Support Comparison
| Browser | JPEG-AI | PGM |
|---|---|---|
Chrome
|
✕ | ✕ |
Firefox
|
✕ | ✕ |
Safari
|
✕ | ✕ |
Edge
|
✕ | ✕ |
IE (Legacy)
|
✕ | ✕ |
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
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
Use JPEG-AI when…
- Machine Vision and AI Workflows
- Cloud Storage Image Optimization
- High-Efficiency Mobile Image Capture
- Visual Surveillance
PGM
Use PGM when…
- Computer Vision and Machine Learning Pre-processing
- Scientific and Medical Image Processing
- Unix/Linux Command-Line Image Pipelines