Wasmrun – A WASM runtime with plugin support (formerly Chakra)

Hacker News

We’ve recently renamed our WebAssembly runtime project from Chakra to wasmrun to avoid naming confusion and to better align with our goals of modularity and extensibility. We just shipped version v0.10.2 which introduces a plugin architecture The first plugin is wasmgo – a simple TinyGo-based Wasm compiler plugin. You can install it with: ``` wasmrun plugin install wasmgo ``` Main crate: https://crates.io/crates/wasmrun GitHub repo: https://github.com/anistark/wasmrun It’s still early days, and we’re actively building. Would love your feedback, thoughts, and contributions. Right now, all discussions are happening on GitHub. Happy to answer questions here too!

Visit product View on Hacker NewsJun 30, 2025

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

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

38%38% 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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: introduce · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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