Image MIME Reference
JPEG-AI
JPEG AI Image
image/jaii
VS
Radiance HDR
image/vnd.radiance
Radiance
A complete technical comparison of JPEG AI Image and Radiance HDR — covering compression, feature support, browser compatibility, magic bytes, and when to choose each format.
Equal browser support
Feature Support
| Feature | JPEG-AI | Radiance |
|---|---|---|
| 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)
Radiance HDR
image/vnd.radiance
Extension
.hdr.pic.rgbe.xyze
Container
Radiance Information Header
Compression
Run-Length Encoding (RLE) / Uncompressed
Algorithm
Adaptive Run-Length Encoding (RLE)
Color Depth
32-bit (8-bit per channel RGB + 8-bit shared Exponent)
Developed by
Greg Ward (Lawrence Berkeley National Laboratory)
Released
1989
Magic Bytes
23 3F 52 41 44 49 41 4E 43 45
Browser Support Comparison
| Browser | JPEG-AI | Radiance |
|---|---|---|
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
Radiance
Radiance Strengths
- Universally supported by almost every 3D modeling software, renderer, and game engine in existence
- RGBE encoding offers a brilliant balance between High Dynamic Range capability and small file size (compared to 32-bit float OpenEXR)
- Simple, easy-to-parse ASCII header followed by straightforward RLE binary data
Limitations
- Does not support alpha transparency (no way to store an isolated light source with a transparent background)
- The shared exponent architecture can occasionally introduce banding or color artifacts in extreme edge cases compared to true 16-bit/32-bit floating-point formats like OpenEXR
- Zero native browser support for 2D viewing
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
Radiance
Use Radiance when…
- Image-Based Lighting (IBL)
- 3D Environment Maps (HDRI Skydomes)
- Lighting Simulation
- VFX and CGI Rendering