Small should be a measurement.
A model’s download size is only one part of its footprint.
Count the complete cost.
The artifact sizes in our catalog are the raw UTF-8 JSON files containing labels, features, and weights. They exclude application code, runtime memory, and any compression applied by a server. We report exactly what we measured so the numbers stay useful.
Different tasks need different models.
A Gaussian classifier over five engineered audio features can occupy less than a kilobyte. That does not make it equivalent to a neural speech model. It reflects the narrower representation and the much simpler training problem.
Make releases reproducible.
The training script uses fixed seeds and deterministic serialization. A manifest records the SHA-256 digest of each artifact. The SDK reads an explicit artifact instead of silently fetching new weights during inference.
Measure the application too.
Before releasing a production SDK, we need device-level latency, peak memory, cold-start behavior, and task quality on independent datasets. Our research preview does not yet claim those measurements.