QVAC by Tether: the Infinite Stable Intelligence Platform

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

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.

Video generation

Text-to-video and image-to-video generation via a customized Diffusion backend.

World simulation

Turn a first-frame image and navigation controls into a streamed, navigable video via an interactive world model.

Music generation

Generate music from text prompts and lyrics via ACE-Step or MiniMax-Music3.

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.

Decisions

Answer choice, ordinal-score, and statement-probability questions about text for routing and evaluation via Laya.

System overview

The SDK is the main entry point for using QVAC. It is type-safe and exposes all QVAC capabilities through a unified interface. Two clients share that interface — JS/TS (@qvac/sdk, running on Node.js, Bare, and Expo) and Python (tetherto-qvac-sdk, asyncio-native) — and both call into the same underlying runtime, so capabilities and behavior are identical either way.

Additionally, QVAC provides a CLI with development tools and an HTTP server that wraps QVAC and exposes an OpenAI-compatible API. You can use the HTTP server as a local model provider to connect any AI tool, harness, or system.

Finally, QVAC also encompasses QV.AC, a desktop and mobile assistant app, to empower users and showcase QVAC capabilities, as well as research initiatives to advance the state of the art in local AI.