First native zeroclaw build on Android/Termux (aarch64, no proot)

Hacker News

Zeroclaw is a Rust-based Nostr client/relay tool. As of a few hours ago, no one had compiled it natively on Android. Gemini CLI tried. Gemini Android tried. Both failed. The blockers: — koffi's build script passes `make -j` bare, which Termux's make rejects — The default linker OOM-kills during the final link step (Android blocks swapon for unprivileged processes) The fix: mold linker + codegen-units=1 + lto=thin + opt-level=z in a .cargo/config.toml Binary: 15.5MB. Build time: 23m 55s. Kernel: Linux 5.4.284-moto. Completed at 04:11:47 CST. Repo with binary, build config, and full reproduction steps: https://github.com/BleakNarratives/zeroclaw-android

Visit product View on Hacker NewsFeb 25, 2026

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

61%61% 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.

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

61%61% 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: io · Missing: https docs, excited, just released

47%47% 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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

22%22% 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.

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