nafnet-gopro-width32 — LiteRT.js demo

Source	https://huggingface.co/litert-community/NAFNet-GoPro-width32-LiteRT
License	mit
Model file	`c267178696fbc39bb1584b1694e755527a8af5e16db9a74b4b8978a7a72dfd9f.tflite` — downloaded from the source at runtime; this site hosts no weights

Run it in your browser

Measured sweep results

Every number is labeled with the environment that produced it — headless desktop Chromium is not a user’s phone, and results are only meaningful together with their environment.

Backend	Status	Full delegation	Output match	Latency p50 (ms)	Environment	Verified	Provenance
`wasm_xnnpack`	pass	—	—	2712.535	mac-studio-m4-max · chromium 151.0.7922.34 headless · macOS · @litertjs/core 2.5.3	2026-08-11	measured
`webgpu_mldrift`	pass	yes	pass	20.842	mac-studio-m4-max · chromium 151.0.7922.34 headless · macOS · @litertjs/core 2.5.3	2026-08-11	measured

Build this yourself

One-line prompt for your AI coding assistant (uses the litert-cookbook web skill):

Use the litert-cookbook web skill to build a LiteRT.js browser demo for nafnet-gopro-width32: load the model from https://huggingface.co/litert-community/NAFNet-GoPro-width32-LiteRT/resolve/main/c267178696fbc39bb1584b1694e755527a8af5e16db9a74b4b8978a7a72dfd9f.tflite (license: mit) and run it with @litertjs/core.

Reproduce this with an agent

One-line prompt for Claude Code / Gemini CLI — re-runs the same sweep verification for this model, locally:

In the edge-compat repo, verify nafnet-gopro-width32 with the sweep harness: write /tmp/catalog.csv with the header line model_id,source,input_spec,license,notes and the single row nafnet-gopro-width32,https://huggingface.co/litert-community/NAFNet-GoPro-width32-LiteRT/resolve/main/c267178696fbc39bb1584b1694e755527a8af5e16db9a74b4b8978a7a72dfd9f.tflite,1x3x256x256:float32,mit, — then run: cd web/sweep && npm ci && npm run sweep -- --catalog /tmp/catalog.csv --out out/ — and compare out/nafnet-gopro-width32.json with the sweep table on this page.