tetherto/qvac
Open-source local AI SDK - run AI on-device with no cloud, no API keys. Supports GGUF, RAG, image, music, and video generation, speech-to-text, P2P inference, and more. Cross-platform: Linux, macOS, Windows, Android, iOS.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
5 releases in the last 90 days, the latest today, with 71 contributors on GitHub.
Gained 66% more stars in the last 90 days than in the 90 days before.
Use Cases & Benefits
- Provides an open-source, cross-platform SDK to run AI models locally and enable peer-to-peer AI inference without cloud dependencies.
- Enables decentralized, local-first AI applications with seamless P2P model sharing and inference, ensuring privacy and offline capabilities.
- Use for building privacy-focused AI apps that run large language models and multimodal AI entirely on-device across multiple OSes.
- Use for developing decentralized AI systems that delegate inference tasks to peers, optimizing resource usage in distributed networks.
- Use for integrating OpenAI-compatible APIs locally to leverage speech-to-text, image generation, and retrieval-augmented generation workflows.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
QVAC is an open-source, cross-platform ecosystem for building local-first, peer-to-peer AI applications and systems. With QVAC, you can run AI tasks like LLMs, speech, RAG, and more locally across Linux, macOS, Windows, Android, and iOS — or delegate inference to peers using its built-in P2P capabilities.
QVAC is composed of JavaScript libraries and tools that converge in the JS SDK. The SDK is the main entry point for using QVAC. It is type-safe and exposes all QVAC capabilities through a unified interface. It runs on Node.js, Bare runtime, and Expo.
Additionally, QVAC provides a CLI with tools and an HTTP server that exposes an OpenAI-compatible API. By implementing the OpenAI API format, QVAC can integrate with the broader AI ecosystem.
Install the
@qvac/sdknpm package in your project. Then load models and run AI inference locally, or delegate inference to peers using the built-in P2P features.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
149+57
Open issues
111+19
Compared with peers in AI
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| thedotmack/claude-mem | 113.6K | +8.8K | 35 | today |
| D4Vinci/Scrapling | 98.1K | +6.9K | 65 | 1 day ago |
| Leonxlnx/taste-skill | 110.7K | +5.2K | 55 | 1 day ago |
| calesthio/OpenMontage | 77.2K | +4.2K | 40 | — |
| heygen-com/hyperframes | 79.6K | +4.1K | 45 | today |
| tetherto/qvac | 744 | — | 40 | today |
| Category median | 98.1K | +5.2K | 45 | — |
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