Determined AI

license

Apache-2.0(OSI

source

public(determined-ai/determined is the open platform)

core-gated

gated(master/internal/license/license.go ships an IsEE() check returning true when a license key and public key are present, so an enterprise edition is unlocked by a key rather than shipped in the open tree)

Apache-2.0 source with an enterprise edition behind a key. The open repository itself carries the gate: master/internal/license/license.go defines IsEE(), which returns true when both a license key and a verifying public key are set. That is functionality unlocked by a key rather than a separate product sold alongside, which is what this dimension asks about.

• https://github.com/determined-ai/determined recorded 2026-09-15

  Repository page for determined-ai/determined: Apache-2.0 license, public and unarchived, last push 2025-03-20. Establishes the license, that the source is public, and the dormancy recorded in comments.

• https://raw.githubusercontent.com/determined-ai/determined/main/master/internal/license/license.go recorded 2026-09-15

  Determined's own license module: IsEE() returns true when publicKey and licenseKey are both set, and SetLicenseAndKey populates them. Establishes that an enterprise edition is gated on a key.

The PyPI download API reports 62,711 downloads of determined in the trailing 30 days, inside the 10K-100K band for level 2.

• https://pypistats.org/api/packages/determined/recent recorded 2026-09-15

  Trailing-window download counts for the declared PyPI artifact: 62,711 downloads in the trailing month.

Band 5 on Determined's own documentation: setting slots_per_trial to 16 means 'two 8-GPU agent machines will be used in a trial', an allocation spanning machines and granted together by Determined's own scheduler over its resource pools. It chooses the machines and holds the set, which is what this band asks for.

• https://raw.githubusercontent.com/determined-ai/determined/main/docs/model-dev-guide/dtrain/dtrain-implement.rst recorded 2026-09-15

  Determined's distributed-training documentation: resources.slots_per_trial enables multi-GPU training, and 'slots_per_trial: 16 # Two 8-GPU agent machines will be used in a trial'.