I486SX_soft_FPU – Software FPU Emulator for NetBSD 10 on 486SX

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First Release is Here! I'm excited to announce the first release of i486SX_soft_FPU — a software FPU emulator for the classic Intel 486SX CPU, running on NetBSD 10! This project brings floating-point support back to life for 486SX machines, even though modern NetBSD versions no longer natively support processors without a hardware FPU. If you're into retrocomputing, operating system hacking, or just love old-school hardware, check it out! Project page: https://github.com/mezantrop/i486SX_soft_FPU Contributions, feedback, and testing are all very welcome! Let's keep these vintage machines alive! #retrocomputing #NetBSD #486SX #opensource

Visit product View on Hacker NewsApr 27, 2025

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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.

best fitHighest predicted score across all platforms for this description.

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

65%65% 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

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: mac, open · Missing: agents, macos, agent

30%30% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

16%16% 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

16%16% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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