gemma-2b-architecture-specs
IN premise — summaries/2026/08/24/park-2024-categorical-hierarchical-concepts-sR-references.md
Created 2026-08-25T02:58:26+00:00
Gemma-2B has 2 billion parameters, was pre-trained on 3 trillion tokens, uses a 256K vocabulary, and has a 2,048-dimensional representation space.
Summary
These specs pin down the hard size and training budget of the Gemma-2B model, setting the ceiling on how much knowledge it absorbed and how many distinct concepts it can juggle internally. For the system, this means any output from that model is bounded by a relatively compact representational space, so its reasoning depth and vocabulary coverage should be treated as constrained rather than open-ended.