I indexed 37h of my videos using an RTX 4090 and local ML models in 24h

Hacker News

TLDR: Following my recent blog post and Hacker News post ( https://news.ycombinator.com/item?id=48528029 ). where I ran the desktop app on my M1 Max. This time, I’m using the self-hosted version, running in Docker, with an NVIDIA RTX 4090 (24 GB of VRAM). The content is also fundamentally more demanding: long podcast episodes with at least two faces in every frame, coding tutorials packed with on-screen text, and screen recordings. GoPro footage is mostly wide outdoor shots. But NVIDIA was much faster than my M1 Max. The longest video was a livestream of 3h 12m indexed in 1h 52m (4,612 frames analyzed). You can directly see the processing jobs results in JSON format here: https://gist.github.com/IliasHad/fd64e4d331e90e57d61e95f64e8...

Visit product View on Hacker NewsJun 30, 2026

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Did not reach leaderboard

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Hacker NewsStrong engagement from HN community · Strong signals: hacker news, ide, io · Missing: https docs, excited, just released

80%80% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal

40%40% 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, revenue

19%19% 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, crypto

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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