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A tool for multimodal model evaluations
Hacker NewsA tool for multimodal model evaluations
We make it easy to run and share evaluations of multimodal models. Most tools focus on language models (LLMs); multimodal models deserve their own evaluation tools. We believe it should be easy to compare models & publicly share evaluations.
Share cardActual performance
4points
Did not reach leaderboard
Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: model, models · Missing: mac, agents, macos86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: lua, io · Missing: https docs, excited, just released57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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