Gemini Embedding 2
Product HuntGoogle's first natively multimodal embedding model
Gemini Embedding 2 is Google's first natively multimodal embedding model that maps text, images, video, audio and documents into a single embedding space, enabling multimodal retrieval and classification across different types of media and it’s available now in public preview.
Share cardActual performance
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Made the leaderboard
Traction signals
Makers1
Launch Intel predictions
Analyze your own launch →Product HuntOn track for Day 1 leaderboard · Strong signals: model, google, single · Missing: mac, agents, macos90%90% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: video, google · Missing: mobile apps, ios, personal56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto13%13% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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