TechFlow reports that on June 1, Tether AI announced the open-source release of TurboQuant, integrating it into QVAC SDK 0.12.0. Built upon Google Research’s memory compression algorithm, TurboQuant compresses the KV cache used during large language model inference by up to approximately 5×, significantly reducing memory consumption on local and edge devices while preserving output quality.
Tether states that TurboQuant enables laptops, smartphones, consumer-grade GPUs, edge devices, and decentralized inference networks to handle longer conversations, larger documents, and more complex workloads—and is now available to developers via Fabric.
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