From Decrypt · By Jose Antonio Lanz
In brief
Tether's new 800-million-parameter BotPsy AI agent outperformed models 2.5 times larger on five of six tool-use benchmarks in company testing.
The model can manage multi-step tasks involving phone settings, messaging and scheduling, potentially without sending personal information to cloud servers.
BotPsy expands Tether's QVAC ecosystem, which already includes local AI models for medical applications, translation and speech processing.
Tether, the company behind the world's largest stablecoin, USDT, is getting surprisingly good at making tiny AI models punch above their weight.
The company on Wednesday unveiled QVAC BotPsy, an 800-million-parameter AI agent designed to carry out everyday tasks on personal devices. Parameters are essentially the knobs that determine how much an AI model can do, and more of them generally translate to improved performance. And for reference, frontier AI models today run in the trillions of parameters.
In the company's own testing, Tether’s relatively tiny model outperformed competitors with up to 2.5 times as many parameters, suggesting that AI assistants may not need enormous models to get things done.
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Anthropic98%YesNoCelonis50%YesNoRemote6%YesNoFreddie Mac6%YesNoRippling5%YesNo+24 more outcomes+23 more outcomes$625.67K volumeCloses: Jan 1, 2027, 04:59 UTCCloses: Jan 1, 2027, 04:59 UTCUnlike traditional chatbots that simply respond to questions, BotPsy is agentic, meaning it’s designed to take action. It can identify which tools an application needs, execute commands in the right order, and adjust when something goes wrong.
For example, Tether described a benchmark scenario in which an AI assistant needed to send a message but encountered two problems: Wi-Fi was disabled and the inbox was full. BotPsy turned on Wi-Fi, cleared enough storage, and completed the task, while the underlying model repeatedly attempted the same failed operation.
That's a fairly mundane achievement, but it's precisely the kind of problem that makes AI agents useful outside a chatbot window.
BotPsy is built on Alibaba's Qwen3.5-0.8B architecture, a relatively small language model that Tether trained further to specialize in interacting with software tools. Its 800 million parameters represent the numerical values the model learned during training, and a smaller parameter count generally means less memory is needed to run it.
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