Tether just dropped a library’s worth of new coursework for its local-first AI platform. Nearly 80 new lessons landed on Tether Academy this week, all built around the company’s QVAC open-source framework and compatible with SDK version 0.17.
The update, announced by developer @thisonedevv on August 13, includes runnable code samples that execute entirely offline on local machines. Among the new additions is a music generation example, a first for the platform that signals QVAC’s ambitions stretch well beyond text-based AI models.
What QVAC actually does
QVAC provides a single API for running AI models locally across Linux, macOS, Windows, Android, and iOS. The framework supports P2P networking and uses Vulkan for hardware-agnostic inference.
Cloud-based AI services from companies like OpenAI or Google require sending data to remote servers, which creates both latency and privacy concerns. QVAC sidesteps both by keeping everything local. Your data never leaves your device unless you want it to.
