Image MIME Reference
FST-Image
FAST Search & Transfer Image
image/vnd.fst
VS
JPEG AI Image
image/jaii
JPEG-AI
A complete technical comparison of FAST Search & Transfer Image and JPEG AI Image — covering compression, feature support, browser compatibility, magic bytes, and when to choose each format.
Equal browser support
Feature Support
| Feature | FST-Image | JPEG-AI |
|---|---|---|
| Transparency (Alpha) | ✕ No | Yes |
| Animation Support | ✕ No | Yes |
| Progressive Loading | ✕ No | Yes |
| HDR Support | ✕ No | Yes |
| EXIF Metadata | ✕ No | Yes |
| ICC Color Profile | ✕ No | Yes |
FAST Search & Transfer Image
image/vnd.fst
Extension
.fst
Container
Proprietary FAST Container
Compression
Proprietary
Algorithm
Unknown (Proprietary FAST encoding)
Color Depth
Unknown
Developed by
FAST Search & Transfer ASA (Arild Fuldseth)
Released
2000
Magic Bytes
Unknown (Proprietary)
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 | FST-Image | JPEG-AI |
|---|---|---|
Chrome
|
✕ | ✕ |
Firefox
|
✕ | ✕ |
Safari
|
✕ | ✕ |
Edge
|
✕ | ✕ |
IE (Legacy)
|
✕ | ✕ |
FST-Image
FST-Image Strengths
- Historically served as an optimized, compressed format for FAST's early multimedia and live streaming engines over constrained late-1990s bandwidth
Limitations
- Completely obsolete and non-functional in modern software ecosystems
- Undocumented, closed-source binary structure with zero support in modern image processing libraries
- Shares its file extension with several other distinct file types (such as FL Studio state files or FAST Search dictionaries), leading to easy misidentification
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
FST-Image
Use FST-Image when…
- Historical FAST Enterprise Search Indexing
- Legacy Proprietary Multimedia Streaming (late 1990s)
- Internal Media Transmission
JPEG-AI
Use JPEG-AI when…
- Machine Vision and AI Workflows
- Cloud Storage Image Optimization
- High-Efficiency Mobile Image Capture
- Visual Surveillance