Google Gemini 3.8 Flash and Cyber
Product HuntNext-gen Gemini for agents, reasoning, and cyber security
Share cardActual performance
248upvotes
2comments
Made the leaderboard
Traction signals
Makers1
Launch Intel predictions
Analyze your own launch →Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, google · Missing: mac, macos, cursor92%92% 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, podcasting58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto52%52% predicted probability of success on BetaList, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue28%28% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Correct prediction on native model
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