As for intelligence, GROC3 incorporates significant advancements in reasoning which are achieved through extensive reinforcement learning. This approach enables the model to process complex problems over several seconds or minutes, refining its solutions by identifying errors, exploring alternative methods, and verifying outcomes. And to showcase these capabilities, two beta reasoning variants named GROC3 and GROC3 Mini were introduced. Testing on the 2025 American Invitational Mathematics Examination, it yielded a score of 93.3% for GROC3 at its highest test-time compute setting. Additional benchmarks include 84.6% on the graduate-level GPQA test for expert reasoning, and 79.4% on live code bench for coding tasks.

As for GROC3 Mini, it achieved 95.8% on American Invitational Mathematics Examination and 80.4% on live code bench, demonstrating efficiency in STEM-focused applications. Users can also access the reasoning process of GROC3 through the Think feature, which provides transparency into its step-by-step problem solving. This functionality is intended to support educational and professional use cases. And in user preference metrics, GROC3 achieved an ELO score of 1,402 on Chatbot Arena, indicating strong performance relative to competing models. But even without its reasoning mode activated, GROC3 still delivers rapid responses thanks to its extensive pre-training on the Colossus supercluster. In fact, it performs competitively across benchmarks including MMLU Pro for general knowledge, GPQA for scientific expertise, and AIME for mathematical proficiency.

Additionally, the model supports multimodal tasks, including image analysis, generation, and video comprehension, with its context window of 1 million tokens being eight times larger than that of previous XAI models, enabling it to process lengthy documents and complex prompts effectively. And on the loft benchmark evaluating long-context retrieval across 12 tasks, GROC3 also achieved leading accuracy scores. An early version of GROC3 internally codenamed Chocolate even previously topped the LM Arena Chatbot Arena leaderboard, outperforming its peers across multiple categories, with XAI planning to further scale its pre-training efforts using the 200,000 GPU cluster with even larger models anticipated in the future.

But XAI has also introduced DeepSearch, its first AI agent integrated with GROC3. Equipped with internet access and code interpreters, DeepSearch is designed to retrieve and analyze information, resolve conflicting data, and produce detailed summaries. The agent targets applications ranging from real-time news aggregation to in-depth scientific research, offering a more advanced alternative to traditional search tools. DeepSearch will be available to users and enterprise partners as part of the upcoming GROC3 API release. As for access, GROC3 is already available to a huge audience, with XAI offering unfiltered answers and advanced capabilities in reasoning, coding, and visual processing through the model’s integration on the X platform, GROC.com, and an iOS app, with an Android version in development.

Plus, users can also leverage GROC3’s real-time insights drawn from X posts and web data, enhancing its ability to decode documents, images, and trends. On top of this, premium and premium plus subscribers on X will be given higher usage limits and early access to features like voice interaction, while free users will have query restrictions, but can still explore its functionality. As for the rollout, XAI says their mission is to empower as many users as possible with intelligence tools to accelerate learning and innovation, and GROC3’s capabilities will likely extend beyond software, with XAI potentially planning to integrate the model into physical systems like its Optimus Robot for both industrial and domestic tasks.

In fact, GROC3’s reasoning skills and expansive context window could enable robots to process detailed instructions, adapt to dynamic environments, and perform complex tasks autonomously. For instance, Optimus might use GROC3 to interpret technical manuals, troubleshoot mechanical issues, or optimize workflows in Tesla’s manufacturing facilities. Furthermore, the model’s multimodal capabilities, such as image analysis, could further enhance robotic perception, allowing systems like Optimus to identify objects and navigate surroundings with greater precision. And with the forthcoming GROC3 API scheduled for release in the coming weeks, the standard and reasoning models will be made available, as well as deep search, facilitating likely integration into robotic platforms in the near future.

Plus, enterprise partners may also leverage these tools to develop applications in fields such as healthcare, logistics, or space exploration. And according to the API’s features of tool use and advanced agent functionalities, GROC3 could also support robotic applications by enabling real-time code execution and task coordination. For enterprise applications, the API release will expand GROC3’s utility, potentially enabling businesses to incorporate its capabilities into operational systems. As for now, GROC3 and its variants are still in active development, with XAI committing to regular updates over the next few months based on user input and performance data. In fact, researchers are already moving toward voice-controlled robotics by integrating GROC3’s forthcoming audio interface with Naveela, a breakthrough framework enabling seamless human-robot interaction.

Naveela, or navigation via vision-language action, employs a two-level system combining vision-language agents with real-time locomotion, allowing robots to execute high-level voice commands like, Hey robot, fetch the tool, and being trained on diverse datasets including human videos, indoor navigation simulations, and question-answering tasks, Naveela’s generalizable model outperforms simulator-reliant methods, achieving robust navigation in real-world settings. To do this, its end-to-end vision-based locomotion is guided by LIDAR and ensures safe movement over rough terrain and near-transparent obstacles, minimizing the sim-to-real gap. As for applications for GROC-powered robots, these could include automated assembly in manufacturing, data-driven diagnostics in medical settings, or even infrastructure development in extraterrestrial environments, which is a priority tied to Elon Musk’s SpaceX initiatives.

However, challenges such as computational costs and the need for robust safety protocols still remain as critical considerations for XAI as they continue moving forward. And while no specific timeline for robot integration is known, industry experts suggest that deployment could occur later this year given Tesla’s history of rapid development cycles. Anyways, will GROC-3 be powering robots by the end of this year? Tell us in the comments, and thanks for watching. [tr:trw].