Image MIME Reference
CGM
Computer Graphics Metafile
image/cgm
VS
JPEG AI Image
image/jaii
JPEG-AI
A complete technical comparison of Computer Graphics Metafile and JPEG AI Image — covering compression, feature support, browser compatibility, magic bytes, and when to choose each format.
Equal browser support
Feature Support
| Feature | CGM | JPEG-AI |
|---|---|---|
| Transparency (Alpha) | Yes | Yes |
| Animation Support | ✕ No | Yes |
| Progressive Loading | ✕ No | Yes |
| HDR Support | ✕ No | Yes |
| EXIF Metadata | ✕ No | Yes |
| ICC Color Profile | Yes | Yes |
Computer Graphics Metafile
image/cgm
Extension
.cgm
Container
CGM
Compression
Uncompressed / Binary / Character / Clear Text
Algorithm
Deflate (in some WebCGM profiles)
Color Depth
8-bit, 16-bit, 24-bit, 32-bit
Developed by
ISO / IEC
Released
1987
Magic Bytes
00 20 (Binary) / 42 45 47 49 4E 20 4D 45 54 41 46 49 4C 45 (Clear Text)
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 | CGM | JPEG-AI |
|---|---|---|
Chrome
|
✕ | ✕ |
Firefox
|
✕ | ✕ |
Safari
|
✕ | ✕ |
Edge
|
✕ | ✕ |
IE (Legacy)
|
✕ | ✕ |
CGM
CGM Strengths
- Strictly standardized by ISO, ensuring long-term archiving and cross-platform compatibility in engineering
- Excellent support for rich metadata, hyperlinks, and technical hotspots via the WebCGM profile
- Can store complex 2D geometry, rasters, and text in a single lightweight file
Limitations
- Multiple encoding schemes (Binary, Character, Clear Text) make parser development difficult
- Zero native support in modern web browsers without third-party plugins
- Largely replaced by SVG for general-purpose 2D vector graphics on the web
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
CGM
Use CGM when…
- Technical Illustrations
- Aerospace & Defense (S1000D)
- CAD/CAM
- Geophysics
JPEG-AI
Use JPEG-AI when…
- Machine Vision and AI Workflows
- Cloud Storage Image Optimization
- High-Efficiency Mobile Image Capture
- Visual Surveillance