Presets & autotune

Longpipe ships five model presets covering different speed/quality tradeoffs. The default ('auto') picks one for the user’s hardware automatically. All five get frame-to-frame stability from the optical-flow head — previous outputs are warped along the predicted motion and blended, with no recurrent state in the network (see Architecture).

The presets

Output resolution is where the matte is produced and composited (the network’s refinement input); base resolution is what the encoder runs at internally (the wrapper strides the input down to it). Frame cadence is how often the model re-runs — skipped frames reuse the previous matte while still compositing every frame, so a 1-in-2 preset costs roughly half the per-source-frame inference of an every-frame one.

large is the design reference tier; the others sit around it as cheaper/heavier variants. Weights are f16 on hardware that supports it (most WebGPU + WebGL2), f32 otherwise — the runtime decides, regardless of preset. All tiers are trained on the same data and exported with the same op fusions. See Architecture for how the encoder, heads and frame skipping fit together.

The three named shortcuts — 'fast', 'balanced', 'quality' — map to xs, medium, xl respectively.

Autotune (preset: 'auto')

On init, the worker microbenchmarks the candidate presets on the real device and picks the largest one whose measured per-frame model cost fits the frame budget — roughly half of a 30fps source frame (~16 ms; WebGL is more conservative, since it has no live upgrade path). The benchmark uses zero-filled weights of the correct shapes (GPU cost is shape-driven), so it runs before any weights are fetched.

Autotune runs once at startup and adds a small amount to init time for the sweep.

Audio denoise auto-selects separately. preset and autotune here govern the video model only. When audio: 'denoise' is set, the denoiser runs its own analogous weight-free probe at init — timing the denoise network on the device (no weights downloaded) to pick dfn / dfnint8 / rnnoise — independent of the video preset. See Audio denoise → Models.

Adaptive (runtime)

When preset: 'auto' and adaptive: true (the default), Longpipe also adjusts at runtime:

• Downgrade if the actual framerate drops below the target (typically because another tab started doing heavy work, the user plugged into a battery-saver power plan, etc.).
• Upgrade if modelMs shows consistent headroom (WebGPU only — WebGL upgrades are too expensive to be worth doing live).

Disable with adaptive: false.

Pinning a preset

new EffectsPipeline(stream, { preset: 'large' })  // disables autotune & adaptive
new EffectsPipeline(stream, { preset: 'auto', adaptive: false })  // autotune once, then stay