Gaussian Splatting from a single photo in ~10 seconds on a Mac Mini

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Last month I posted Mukbang 3D on here but I didn't get any discussion so I thought I'd give it another crack since I've put a bunch more into it. Since last time, I've replaced the video-to-3D pipeline with single-image Gaussian Splatting. A photo now generates in ~10 seconds on a Mac Mini, down from 15-120 seconds for video. You can compare the two approaches—video-based meshes: https://mukba.ng/discover/#videos vs image-based splats: https://mukba.ng/discover/#images Benchmarks for SHARP between Mac Mini M4 and Macbook Pro M4: https://mukba.ng/blog/2026-01-21-sharp-apple-silicon-benchma... I've also optimized rendering speed: I've chunked and zstd'd the output so it can start rendering as soon as the first packet comes in. Why food? I started with Structure from Motion on video, and food was a good constraint because it doesn't move. People look terrible when they blink or shift mid-capture. Now that doesn't matter as much.

Visit product View on Hacker NewsJan 28, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, apple, single · Missing: agents, macos, agent

69%69% 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.

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

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

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

54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, pipe, io · Missing: https docs, excited, just released

42%42% 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 · Strong signals: soon · Missing: plus, platform, intuitive

29%29% 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

17%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, 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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