
SpaceXAI just released Grok 4.5. The company calls it its smartest model to date. It targets coding, agentic tasks, and knowledge work. SpaceXAI says Grok 4.5 was trained alongside Cursor, an AI coding editor. TL;DR Grok 4.5 targets coding, agentic tasks, and knowledge work, trained alongside Cursor. In SpaceXAI’s own chart, Fable (max) leads all four benchmarks; Grok 4.5 is closest on Terminal Bench 2.1. Token efficiency is the standout: about 4.2× fewer output tokens than O
SpaceXAI released Grok 4.5, a general-purpose AI model trained for coding, agentic tasks, and knowledge work, developed in collaboration with an AI coding editor. The model was trained on tens of thousands of GPUs using datasets spanning coding, science, engineering, and math, with reinforcement learning applied across hundreds of thousands of tasks focused on software engineering and technical work. In benchmark tests, Grok 4.5 ranked first on a legal agent benchmark and achieved notable token efficiency, using approximately 4.2 times fewer output tokens than a comparable leading model on one standard test. The model is priced at $2 per million input tokens and $6 per million output tokens, and is available through multiple platforms including a coding editor on all plans and a console API.

OpenAI's new family of models will continue to power Microsoft's suite of workplace and productivity apps.

Today, Meta Superintelligence Labs released Muse Spark 1.1. Alongside it, Meta opened a public preview of the Meta Model API. That second part is the structural change. Meta’s models previously reached developers mainly as open weights. Muse Spark 1.1 is closed, hosted, and metered per token. So the question is narrow. Where does it belong in a stack you already run? What is Muse Spark 1.1? Meta describes it as a multimodal reasoning model built for agentic tasks. Reported gains ove

OpenAI's latest family of models promises improvements across a range of areas, including cybersecurity.
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