Pairing Google Antigravity with Gemini 3.7 Flash solves notable multi-agent math and engineering problems.

In Google Antigravity, we recently launched a number of updates to Teamwork, a framework that allows autonomous teams of AI agents to collaborate, critique, and iterate over hours or days to solve complex, long-horizon challenges. Pairing Gemini 3.7 Flash with this multi-agent orchestration accelerated problem solving across research and engineering:

• Math and theoretical computer science: Solved seven open problems across top venues (FOCS, JMLR) — including Knuth’s Cycles Conjecture (verified in Lean with 40+ page proofs), sparse convex optimization, provable LLM quantization, and prefix-matrix factorizations — while achieving 71% on TCSBench.
• Systems engineering: Built a cycle-accurate, out-of-order RISC-V CPU simulator from scratch that boots the xv6 operating system to shell with 0.71% cycle alignment error against hardware ground truth.
• Open-source software: Landed performance optimizations upstream in core libraries, including Eigen (SIMD fast-paths) and ParlayHash (2x insert throughput, 25% memory reduction).

Read about all the wins on the Antigravity blog.