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CineWan – video generation platform powered by Wan2.2 AI model

Hacker News

CineWan – video generation platform powered by Wan2.2 AI model

I've been working on CineWan, an AI video generation platform that leverages the new Wan2.2 models with Mixture-of-Experts (MoE) architecture. Technical highlights: • MoE architecture separates denoising across timesteps with specialized expert models • Dynamic routing system selects experts based on content complexity • Generates up to 720p, 121-frame videos from text or images • Built on Next.js 15 with edge runtime for <50ms global response times • Smart cost optimization: Cloudflare R2 storage with 3-day auto-expiration • Real-time progress streaming with exponential backoff polling The Wan2.2 models were trained on +65% more images and +83% more videos than v2.1, with integrated cinematography principles. We're seeing cinema-grade output quality that rivals much more expensive solutions.

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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, new, models · Missing: mac, agents, macos
82%82% 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 · Strong signals: para · Missing: supports, reddit linkedin, podcasting
80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: video, para · Missing: mobile apps, ios, personal
63%63% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
42%42% predicted probability of success on AppSumo, 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 released
39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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