# QVAC by Tether: the Infinite Stable Intelligence Platform (/) import { MessagesSquare, Hash, Languages, Mic, Speech, Volume2, ScanText, Image as ImageIcon, Video, GalleryHorizontal, FlaskConical, ScanSearch, Shapes, Eye, Brain, Map, Rocket, Server, MonitorPlay } from 'lucide-react' ## Why QVAC? QVAC is Tether's answer to centralized AI by ensuring AI is not tied to massive data centers in the hands of a few *but is free to run on everyone's devices, without a central point of failure or arbitrary censorship*. ## Features ## AI capabilities {/* : for via */} {/* : for , via */} Text generation}> LLM inference for text generation and chat via Fabric LLM. Text embeddings}> Vector embedding generation for semantic search, clustering, and retrieval, via Fabric LLM. RAG}> Out-of-the-box retrieval-augmented generation workflow. Fine-tuning}> Adapting LLMs to domain-specific tasks via LoRA. Multimodal}> LLM inference over text, images, and other media within a single conversation context. Image generation}> Text-to-image and image-to-image generation via a customized Diffusion backend. Transcription}> Automatic speech recognition (ASR) via a customized Whisper backend or NVIDIA Parakeet. Text-to-Speech}> Speech synthesis (TTS) via a customized GGML backend. Voice assistant}> Real-time voice pipeline: transcription, text generation, and speech synthesis in one loop. Translation}> Text-to-text neural machine translation (NMT), via Fabric LLM and Bergamot. BCI}> Brain–computer interface transcription via a customized Whisper backend. VLA}> Vision-language-action for robot control via a customized GGML backend. OCR}> Optical character recognition for extracting text from images via ONNX Runtime. Image classification}> Classify images into labels with confidence scores via a customized GGML backend. ## System overview {/* Two theme-specific copies of the same diagram, swapped by the site's `.dark` class. The diagram is a draw.io SVG that colors strokes/text via `light-dark()`, which resolves against the SVG document's own `color-scheme`. Because the SVG is embedded in an isolated `` document, the site's class-based theme does NOT reach into it — and Safari (unlike Chromium) won't propagate the embedding context's color-scheme, so dark theme rendered black-on-black. Each copy hard-codes its root `color-scheme` (light vs dark) so `light-dark()` resolves deterministically in every browser; we then show the matching copy via `dark:`/`hidden`. NOTE: temporary fix — the two SVGs differ only by that one `color-scheme` token (regenerate the dark one from the light one). A single-source inline solution is the planned follow-up. */} System overview diagram System overview diagram *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](https://bare.pears.com), and [Expo](https://expo.dev). Additionally, QVAC provides a CLI with development tools, as well as an HTTP server that wraps QVAC and exposes an [**OpenAI-compatible API**](https://platform.openai.com/docs/api-reference). *By implementing the OpenAI API format, QVAC can integrate with the broader AI ecosystem.* Finally, QVAC also encompasses desktop and mobile [**flagship applications**](https://qvac.tether.io#products) to empower users and showcase QVAC capabilities, as well as [**research initiatives**](https://huggingface.co/qvac) to advance the state of the art in local AI. ## Next steps Choose how you want to start with QVAC: } title="Get started with the SDK"> Learn the essentials for using the SDK: system requirements, compatibility matrix, setup basics, and core usage flows. } title="Quickstart"> Run your first example using the JS/TS SDK. At the end, you'll find instructions to run any example in this documentation. } title="See QVAC in practice"> Try QVAC Workbench, our flagship desktop and mobile app built with QVAC. } title="Integrate an OpenAI-compatible client"> Run the QVAC HTTP server and connect any existing OpenAI-compatible system to local AI.