We

We Built a "Nano Banana" for 3D Editing

Hacker News

We Built a "Nano Banana" for 3D Editing

Most 3D AI tools force you to start from scratch every time you want to make a change. Anyone who’s used 3D AI has seen this: fix the hands, the toes break. Or you download a model and only need to tweak one part, not redo the entire asset. That’s the problem we’re trying to solve. We just launched an editing feature in our 3D AI tool, Rodin. It lets you edit existing 3D models by selecting an area and typing your prompt, without rebuilding everything. You can upload any model, or generate one from Rodin, and change only the part you want. For example: “Replace the head of this Gundam model with Crayon Shin-chan’s head.” This came from working with real production pipelines, where fast iteration matters more than one-shot perfection. Demo: https://youtu.be/-5_sSHeOmuc You can try it with this code for a 14-day Creator Plan: ME8EW4PMCRT4 Happy to answer any questions.

Visit product View on Hacker NewsJan 30, 2026

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

90%90% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, pipe · 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.

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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

28%28% 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

18%18% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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