The Jev demo uses Google DeepMind's EmbeddingGemma2 as a real-time system endpoint with 20ms latency for text and 100ms for images. It supports real-time training and can distill knowledge from upstream teacher models.

Name: The Jev demo uses Google DeepMind's EmbeddingGemma2 as a real-time system endpoint with 20ms latency for text and 100ms for images. It supports real-time training and can distill knowledge from upstream teacher models.
Uploaded: 2026-10-27T16:00:43.922Z
Channel: mmastrac
Description: The Jev demo uses Google DeepMind's EmbeddingGemma2 as a real-time system endpoint with 20ms latency for text and 100ms for images. It supports real-time training and can distill knowledge from upstream teacher models.

mmastracinfra-sdks-integrations190.7K views · 2.4K likes

Discovered 2026-10-27, refreshed 2026-11-05. Descriptions and stats are pulled from the project's own X post and refreshed automatically — they aren't independently verified by JevTracks beyond the initial eligibility check.