Hydra AI is a new way to build AI. Instead of one giant model trying to do everything, Hydra AI runs many models together, like the heads of a hydra. For each of hundreds of kinds of request, from coding to writing to research to advice, it keeps a playbook: which models to use, how to combine them, and how to check the result. Code is run and tested, apps are opened and clicked through, and facts are checked against their sources. Every mistake becomes a proposed fix, and a fix goes live only when it beats the old playbook in head-to-head testing. So Hydra AI keeps getting better without retraining a model.
Lucy is the first frontier-level model built with the Hydra AI method, and it's powered by Bittensor.
Try Lucy →Same graders for both.
| Benchmark | Lucy | Open frontier model |
|---|---|---|
| Instruction following (IFEval) | 94.0% | 91.5% |
| Live coding problems solved (LiveCodeBench, of 175) | 157 | 141 |
| Real GitHub bug fixes solved (SWE-bench Verified, of 500) | 427 | 408 |
IFEval and SWE-bench Verified were run on Oct 19, 2026; LiveCodeBench on Oct 20, 2026. Both models were run on the same harness and graded with the same grader. Lucy routes each request across several models: in the SWE-bench Verified run about 91% of Lucy's model calls were served by DeepSeek V4.1 Flash and about 8% by Kimi K3.
Full benchmark comparison: tao1.ai/about