VidFlux – Generate videos using AI models like Veo3, Sora2,and Wan 2.5

Hacker News

Hi everyone I built vidflux.ai — a unified AI video generation platform that lets you create videos using multiple top-tier models in one place: Veo3, Sora2, Kling, Wan 2.5, and Seedance. You can upload an image or text prompt, choose a model, and instantly generate short clips for creative storytelling, product demos, or experiments. I was inspired by how fragmented AI video tools have become — each model has a different interface, format, and API. VidFlux aims to simplify this by giving creators one consistent workspace. Would love your feedback on: - Which models or features should be added next? - How should pricing or credits work for fair usage? Try it here: https://vidflux.ai Thanks for checking it out!

Visit product View on Hacker NewsOct 27, 2025

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

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best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: model, models, using · Missing: mac, agents, macos

87%87% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: video · Missing: mobile apps, ios, personal

58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: platform, interface · Missing: plus, intuitive, reviews

53%53% 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, revenue

20%20% predicted probability of success on Acquire.com, 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

16%16% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

BetaListMay not resonate with beta-testers · 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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