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A fast, privacy-first image converter that runs in browser

Hacker News

A fast, privacy-first image converter that runs in browser

Hey HN I built ImageConverter.dev because I got tired of “free” image converter sites that force uploads, or throttle conversions. So I made a tool that runs 100% client-side — meaning your images never leave your device. It’s built for speed, simplicity, and privacy. What it does Convert images between JPG, PNG, WebP Works offline once loaded (PWA support) How it works It uses the Canvas API and WebAssembly to handle conversions directly in the browser. There’s no upload, no tracking, no server costs, and it’s fast even on mid-range devices. Why I built it I wanted an instant, no-ads, privacy-safe way to handle images for my personal projects — something lightweight enough to replace desktop tools. Try it https://imageconverter.dev Would love feedback from the community — especially on: Performance on different browsers/devices Thanks for reading!

Visit product View on Hacker NewsOct 24, 2025

Actual performance

48points

38comments

Made the leaderboard

Launch Intel predictions

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

56%56% 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.

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

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

44%44% 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: ide, io · Missing: https docs, excited, just released

29%29% 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 · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs

22%22% 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

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

Incorrect prediction on native model

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