According to Sundar Pichai on X, Google launched two updates to Gemini API’s Deep Research: improved quality with MCP support and native chart or infographics generation, plus a Max mode for extended test-time compute that achieves 93.3% on DeepSearchQA and 54.6% on HLE (source: Sundar Pichai). As reported by Sundar Pichai, businesses can use Deep Research for faster synthesis and use Max to maximize retrieval depth and reasoning quality, improving enterprise workflows like competitive analysis, technical due diligence, and KPI reporting with auto-generated visualizations. According to Sundar Pichai, the MCP integration enables structured tool or data access, streamlining multimodal querying and programmatic research pipelines for product teams building analytics copilots and research agents.

According to Demis Hassabis on X (Twitter), Google DeepMind’s Gemini 3 Deep Think achieved 84.6% on ARC-AGI-2, 48.4% on Humanity’s Last Exam without tools, and a 3455 Elo rating on Codeforces, setting new records in math, science, and reasoning benchmarks. As reported by the post, these scores signal stronger generalization and competitive programming ability, which can translate to higher reliability in enterprise workflows like scientific analysis, code synthesis, and automated testing. According to the announcement, outperforming prior state-of-the-art on ARC-AGI-2 and reaching 3455 Elo positions Gemini 3 Deep Think as a top contender for tasks demanding multi-step reasoning, offering businesses opportunities to cut cycle times in R&D, accelerate software delivery, and reduce inference retries in production LLM pipelines.