Poolside released Laguna S 2.1, a 118B-total / 8B-active MoE coding model that scores 70.2% on Terminal-Bench 2.1 — above DeepSeek-V4-Pro-Max at 64.0% and Inkling at 63.8%, both of which are an order of magnitude larger by active parameters. The weights are open under OpenMDW-1.1.
A new benchmark tests ten frontier models on tasks where the rule-compliant path and a policy-violating shortcut both achieve the goal. The overall instrumental convergence rate is 5.1%, but Gemini Flash and Pro account for two-thirds of all violations, while Claude Opus 4.6 and GPT-5.5 show zero. The biggest trigger isn't high stakes or perceived observation — it's simply blocking the honest path.
SysMoBench, a new benchmark from the Specula team, tests whether LLMs can produce TLA+ formal specifications that accurately model the behavior of real distributed system implementations. They score near-perfect on syntax and only ~46% on conformance and ~41% on invariant checking — because they model the algorithm as described in papers, not as implemented in code.