# joey-1

Base Labs released joey-1, a 2B decision model that answers label-style calls such as routing a ticket or flagging a message by returning a single token and a calibrated probability in one forward pass, instead of generating text. At production scale it serves the average 2,000-token request at a P50 end-to-end latency of 20 ms, about 2.5x faster than elephant-1 at 49 ms, and at $0.01 per million tokens it costs a tenth of mammoth-1.

Base Labs released joey-1, a 2B decision model that answers label-style calls such as routing a ticket or flagging a message by returning a single token and a calibrated probability in one forward pass, instead of generating text. At production scale it serves the average 2,000-token request at a P50 end-to-end latency of 20 ms, about 2.5x faster than elephant-1 at 49 ms, and at $0.01 per million tokens it costs a tenth of mammoth-1.