Text→Image mean (R@1)
We haven't written a description for this benchmark yet; see the card notes below for how each maker ran it.
- ModelScoreYour cost / mo
- 1Gemini Embedding 2 · Google80.5 score
“Best value”: no other model here reports a higher score at a lower cost for your workload. Scores are self-reported by each maker with different settings, so treat close calls as ties.
How each maker reported it
- Gemini Embedding 2 technical report, Tables 1–2
Google's own numbers. Competitor scores are partly measured by Google through public APIs, partly self-reported. Table 1 overall mean is over tasks where all four models have scores. 'Gemini Embedding (previous)' is the earlier text-only model. Nova MME reported only the MTEB(Multilingual) task mean. Native-audio MSEB passage retrieval: 73.99 MRR@10 vs 70.40 with ASR transcripts (Table 3).
Only each model's own maker's number is shown; scores a maker reports for rival models are left out.