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Market News

Tether Tests QVAC AI: 100% Local Inference on Asana

CEO Paolo Ardoino demonstrates QVAC AI assistant performing fully local reasoning on consumer GPUs, with MCP integration and upcoming open-source code.

Written By:
Vanshita Kanjani

Reviewed By:
Shubham Soni

Last updated: February 13, 2026 10:39 AM
Published 2026-02-12
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Last updated: February 13, 2026 10:39 AM
Published 2026-02-12
Tether Tests QVAC AI 100% Local Inference on Asana

Key Highlights

  • Tether’s new assistant shows that AI automation can run privately on basic consumer hardware without cloud dependency.
  • The system uses the Model Context Protocol (MCP) to bridge local reasoning with professional productivity tools like Asana.
  • An upcoming open-source release aims to decentralize AI access and provide a transparent alternative to centralized corporate models.

Tether CEO Paolo Ardoino revealed the results of live tests conducted on the company’s newly developed QVAC AI Assistant. The development marks Tether’s entry into the decentralized AI space, focusing on privacy and hardware accessibility rather than centralized cloud computing.

In an X post on Thursday, Ardoino showed the assistant working with the Model Context Protocol (MCP) to manage professional activities and functions, including task creation in Asana. The assistant has the capability to perform complex administrative operations through local inferences on consumer-grade computer devices.

Testing Tether's QVAC AI Assistant
many skills already supported via MCP, using Asana in the example below (on a sub-average laptop GPU)
100% local inference/reasoning
soon opensource pic.twitter.com/sYi91QhjVC

— Paolo Ardoino 🤖 (@paoloardoino) February 12, 2026

The demo highlighted the AI’s ability to carry out multi-step operations with a sub-average laptop GPU. This proved that high-level reasoning does not need large server farms. 

During the test, the QVAC interface processed a request for the organization of a project release. As a result, the system generated a main task and a subtask using the Asana productivity tool.

High-performance metrics

The system’s internal thinking process was reflected through the model thinking toggle buttons before the tool call process. The metrics reflected through the terminal for the efficiency of the model included a time of 1062.1 ms to generate the first token and a speed of 34.6 tokens per second.

Over the past year, Tether has invested more in telecommunications, energy production, and artificial intelligence infrastructure. Ardoino has previously argued for the need for independent, peer-to-peer technology that lessens reliance on big tech companies. Tether first launched QVAC AI in May 2025 and further expanded the QVAC Genesis II AI Dataset to 148 billion tokens in December 2025.

By creating an assistant that operates entirely on a user’s local machine, Tether aims to address rising concerns about data privacy and the risk of censorship with centralized AI models.

QVAC as open source

As for the future potential of the technology, it will likely focus on making AI agents more accessible. Ardoino confirmed that the QVAC AI Assistant will become open-source. 

Developers will have the opportunity to examine the code and implement custom solutions by using the model context protocol. Assuming that the performance of the tool is sustained on low-end hardware, it might help to make it more accessible to individuals in areas where internet connection is scarce or to those who cannot afford high-end computing hardware. 

It operates via the MCP, meaning it might support other third-party applications other than Asana. In turn, it can serve as a localized alternative to mainstream AI agents in enterprise environments. 

Independent technology development 

The QVAC AI Assistant testing is a huge step for Tether, which is changing from a financial services provider to a developer of independent technology. The company was able to develop a working prototype of local and independent AI with 100% local inference and reasoning on a standard laptop.

The upcoming open-source release will be the ultimate test of whether this tool can attract interest from the broader developer community and provide a feasible path for decentralized digital assistants.

Also Read: Tether Introduces Searchable Directory for USDâ‚® Services

Disclaimer: The information researched and reported by The Crypto Times is for informational purposes only and is not a substitute for professional financial advice. Investing in crypto assets involves significant risk due to market volatility. Always Do Your Own Research (DYOR) and consult with a qualified Financial Advisor before making any investment decisions.

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Vanshita Kanjani - Crypto Journalist
By Vanshita Kanjani
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Vanshita Kanjani is a crypto journalist, particularly focused on delivering clear insights into regulatory frameworks and industry updates. Her educational background in English literature and prior experience at a local publication house give her a strong foundation for delivering in-depth market analysis and reports.
Shubham Soni Crypto Content Editor
By Shubham Soni
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Shubham Soni is a veteran content editor and journalist with over three years of experience leading digital editorial strategies across the U.S. and Indian markets. With a background in high-pressure newsrooms, Shubham specializes in the rigorous fact-checking, structural editing, and narrative development of complex news and explainers. Throughout his career at prominent digital publications like Sportskeeda and Opoyi, he has managed fast-paced desks covering global politics, sports, and entertainment. His expertise lies in transforming technical information into accessible, high-impact reporting while maintaining strict adherence to editorial ethics and accuracy. At The Crypto Times, Shubham oversees the editorial workflow, mentoring writers to ensure all cryptocurrency research and analysis meets the highest standards of clarity and journalistic integrity.

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