Benchmark Almanac

EmbeddingGemma 2

EmbeddingGemma 2.

Google DeepMind Released October 6th, 2026 Compare with others
4
Benchmarks with a score
0
Ranked first, out of five or more models
0
In the top three
Google DeepMind Oct 2026

EmbeddingGemma 2

Open weights

No Epoch Capabilities Index score yet

Where it ranks

Its best score on each benchmark, and where that ranks among every model with a score there. We rank each model once, at its best setting.

Vision, audio and robotics

BenchmarkScoreRankSource
MMEB-V2 57.3% #3 of 3 Lab model card
MSEB 69.5 #2 of 2 Lab model card
MAEB 49.9 #1 of 1 Lab model card
MIEB Lite 65.7 #1 of 1 Lab model card

Its lab's numbers next to 2 leaderboards

Where the benchmark's own leaderboard, or Epoch AI's run, also has this model. Gaps mostly come from different harnesses, effort levels and task subsets. Every pair.

Benchmark Lab says Board says Gap
MIEB Lite 65.7 MIEB lite, Mean(TaskType), full precision, 768d 63.5 Leaderboard +2.15
MAEB 49.9 MAEB, Mean(Task), full precision, 768d 49.3 Leaderboard +0.56

Its launch post

The benchmarks the lab chose to headline, with the scores it gave.

Its system card

Every result in the longer documents the lab published with it. 4 of them aren't in the launch post.