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Grok 4.1's enhanced emotional intelligence and creativity are now available, rolling out silently since November 1 with rigorous testing to ensure seamless integration across platforms.
Grok 4.1 is now available to all users on grok.com, 𝕏 (formerly Twitter), and the iOS and Android apps. The model is rolling out immediately in Auto mode and can be explicitly selected as “Grok 4.1” in the model picker.
Before its official release, Grok 4.1 underwent a silent rollout from November 1 to 14, 2025. During this period, preliminary builds were gradually introduced to an increasing share of production traffic across grok.com, 𝕏, and mobile applications. Continuous blind pairwise evaluations were conducted on live traffic to ensure the model's performance met our high standards.
Grok 4.1 introduces notable enhancements in creative, emotional, and collaborative interactions. Here are the key improvements:
To achieve these improvements, we leveraged our large-scale reinforcement learning infrastructure from Grok 4. We optimized the model's style, personality, helpfulness, and alignment using non-verifiable reward signals. Here’s a breakdown of the technical approach:

Compared to its predecessor, Grok 4.1 is preferred in blind evaluations:
Grok 4.1 sets a new standard in blind human preference evaluations, as evidenced by its performance on the LMArena Text Leaderboard:
quasarflux) holds the #1 overall position with 1483 Elo, leading by 31 points over the highest non-xAI model.tensor), which uses no thinking tokens for immediate responses, ranks #2 at 1465 Elo. This version surpasses every other model’s full-reasoning configuration on the public leaderboard.Grok 4.1 excels in emotional intelligence, a critical aspect for human-like interactions:
The release of Grok 4.1 marks a significant step forward in AI models' real-world usability, particularly in creative, emotional, and collaborative interactions. With enhanced perception, compelling conversational skills, and coherent personality, Grok 4.1 sets a new standard for AI performance.
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About the author
Kai built ML infrastructure at a Bay Area startup before developing an obsession with transformer architectures and inference optimisation that eventually pulled him out of product work entirely. A stint at a compute research lab sharpened his instinct for what actually matters in a model release versus what is marketing. He writes from the inside — from the perspective of someone who has debugged the systems he is describing at three in the morning. He is allergic to hype and instinctively drawn to the unglamorous plumbing questions that everyone else skips over.
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