QVAC by Tether: the Infinite Stable Intelligence Platform
A local AI SDK for building cross-platform, P2P applications and systems.
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.
Music generation
Generate music from text, lyrics, and musical controls via ACE-Step.
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
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.
Next steps
Choose how you want to start with QVAC:
Get started
Learn the essentials for using the SDK: system requirements, compatibility matrix, setup basics, and core usage flows.
JS/TS SDK
Install @qvac/sdk, run the quickstart, and target Node.js, Bare, or Expo.
Python SDK
Install tetherto-qvac-sdk, run the quickstart, and drive the same worker from Python.
See QVAC in practice
Try QV.AC, our flagship desktop and mobile assistant app built with QVAC.
Use QVAC as a local model provider
Run the QVAC HTTP server and connect it to any OpenAI-compatible tool, harness, or system.