Bespoke Labs launched Nimble-v4 and Nimble-v4-max decision models and said they outperform Jev on Decision Index scores.
On Decision Index, nimble-v4-max scored +10.5 versus Jev 1.13 (and nimble-v4 scored +5.74).
The release adds two higher-performing decision models for users to try for free in its console.
Memento 3, a frozen-LMM agent, continually updates a natural-language rulebook by observing environment transitions, revising hypotheses, compiling executable prediction/planning code, and verifying code fidelity via replay. It reached a mean Relative Human Action Efficiency (RHAE) of 100.0 on ARC-AGI-3, clearing all levels across 25 public games while using 44% of the human action count. This changes learning by shifting from fixed behavior to validated, recursive self-improvement of an explicit world model without changing the underlying LLM.
Artificial Analysis benchmark standings place Opus 5.5 slightly ahead of Wonder Full on the index reported by VentureBeat. Opus 5.5 scores just above Wonder Full on that Artificial Analysis benchmark. Wonder Full is limited to Muse Code plans with no token API access, while Opus 5.5 has comparatively broader availability.
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