QVAC SDK, a universal JavaScript SDK for building local AI applications
Details
- External ID
- 47708697
- Source
- HN
- Company
- —
- Product
- —
- Website domain
- —
- Launched
- April 9, 2026
- Cohort
- —
- Upvotes
- 30
- Upvotes percentile
- 0.794344473007712
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:26 p.m.
- Updated at
- Sept. 7, 2026, 9:26 p.m.
Description
Hi folks, today we're launching QVAC SDK [0], a universal JavaScript/TypeScript SDK for building local AI applications across desktop and mobile.The project is fully open source under the Apache 2.0 license. Our goal is to make it easier for developers to build useful local-first AI apps without having to stitch together a lot of different engines, runtimes, and platform-specific integrations. Under the hood, the SDK is built on top of QVAC Fabric [1], our cross-platform inference and fine-tuning engine.QVAC SDK uses Bare [2], a lightweight cross-platform JavaScript runtime that is part of the Pear ecosystem [3]. It can be used as a worker pretty much anywhere, with built-in tooling for Node, Bun and React Native (Hermes).A few things it supports today: - Local inference across desktop, mobile and servers - Support for LLMs, OCR, translation, transcription, text-to-speech, and vision models - Peer-to-peer model distribution over the Holepunch stack [4], in a way that is similar to BitTorrent, where anyone can become a seeder - Plugin-based architecture, so new engines and model types can be added easily - Fully peer-to-peer delegated inference We also put a lot of effort into documentation [5]. The docs are structured to be readable by both humans and AI coding tools, so in practice you can often get pretty far with your favorite coding assistant very quickly.A few things we know still need work: - Bundle sizes are larger than we want right now because the current packaging of Bare add-ons is not as efficient as it should be yet - Plugin workflow can be simpler - Tree-shaking is already possible, but at the moment it still requires a CLI step, and we'd like to make that more automatic and better integrated into the build process This launch is only the beginning. We want to help people build local AI at a much larger scale. Any feedback is truly appreciated! Full vision is available on the official website [6].References:[0] SDK: http://qvac.tether.io/dev/sdk[1] QVAC Fabric: https://github.com/tetherto/qvac-fabric-llm.cpp[2] Bare: https://bare.pears.com[3] Pear Runtime: https://pears.com[4] Holepunch: https://holepunch.to[5] Docs: https://docs.qvac.tether.io[6] Website: https://qvac.tether.io
Enrichment
- Theme
- browser automation and scraping for AI
- Vertical
- Horizontal
- Function
- Model & infra
- Audience
- Developer
- AI stance
- AI-native
- Project type
- Commercial product
- Normalized one-liner
- javascript sdk for local ai applications
- Manually corrected
- False
Could you build this?
No Creating a unified cross-platform JavaScript SDK that runs local AI models across desktop and mobile requires complex native compilation and hardware acceleration plumbing.
What it would actually take: The architecture requires binding C++ inference engines (such as llama.cpp or ONNX Runtime) to JavaScript via WebAssembly, WebGPU, Node-API, and React Native native modules. The primary challenges are cross-platform hardware acceleration, unified memory management under constrained mobile limits, and OS-level thread scheduling. This requires specialized systems programmers with deep native C++, GPU shader, and mobile platform expertise.
Discussion
16 comments analyzed.
Competitors mentioned: llama.rn (React Native inference via JNI), mesh-llm, Other local inference runtimes/SDKs
Concerns raised: Privacy/safety risks with large codebases and internal tools, Context leakage on real private systems, Unclear incentive structure for node participation, Ambiguous documentation on permission/account requirements, Unclear entry point for developers
Feature requests: Clearer documentation on permission boundaries, Better tutorials beyond LLM chat examples, Specify node payment mechanism in decentralized model
Competitors
Other products that read as similar to this one — 47 launches clear the similarity bar, closest 8 shown.
Attention rank: #8 of 48 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 156 days after the earliest competitor.
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Other launches for this product
- No other launches for this product.
Same idea, different domain
Nobody's really built a model & infra tool for Fintech yet.