image generation
Fast-SRGAN
Small SRGAN-style super-resolution model trained on DIV2K, published as an NXP eIQ model zoo recipe for real-time upscaling.
Levelmodel
Classimage generation
Parameters168K
Contextnot in the notes
Releasednot in the notes
Opennessunknown
Runs onmobile or NPU
Statusactive
R&D Topics
Identity
- Developer
- not in the notes
- Family
- not in the notes
- Released
- – sources
- Weights published
- –
- Record checked
- 12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- CNN
- Total parameters
- 168K sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- image
- Output
- image
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- unknown
- Licence
- not in the notes sources
- Access routes
- open weights download
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- mobile or NPU
- Footprint
- NXP eIQ lists 168K parameters, 240 KB INT8, compatible with i.MX 8M Plus and i.MX 93.
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
Developersnone recorded
ModelFast-SRGANimage generation
R&D TopicsImage and Video Restoration and Super-ResolutionEfficient Vision Networks for Mobile and Edge Devices
Use Casesnone recorded
Who Runs Itnone recorded
R&D topics 2
Efficient Vision Networks for Mobile and Edge DevicesSmall, fast vision networks, often found by architecture search, that run on phones, came…produced byImage and Video Restoration and Super-ResolutionRemoving blur, noise and compression damage and raising the resolution of photos and vide…produced by
Sources
- github.com/NXP/eiq-model-zoo/tree/main/tasks/vision/supe... https://github.com/NXP/eiq-model-zoo/tree/main/tasks/vision/super-resolution
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Fast-SRGAN", https://aurion.semai.id/models/fast-srgan/, records of October 2026.