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Person: "oriol_vinyals"
Gemini 3 Pro — new GDM frontier model 6, Gemini 3 Deep Think, and Antigravity IDE
gemini-3-pro gemini-2.5 grok-4.1 sonnet-4.5 gpt-5.1 google google-deepmind multimodality agentic-ai benchmarking context-window model-performance instruction-following model-pricing api model-release reasoning model-evaluation sundarpichai _philschmid oriol_vinyals
Google launched Gemini 3 Pro, a state-of-the-art model with a 1M-token context window, multimodal reasoning, and strong agentic capabilities, priced significantly higher than Gemini 2.5. It leads major benchmarks, surpassing Grok 4.1 and competing closely with Sonnet 4.5 and GPT-5.1, though GPT-5.1 excels in ultralong summarization. Independent evaluations from Artificial Analysis, Vending Bench, ARC-AGI 2, Box, and PelicanBench validate Gemini 3 as a frontier LLM. Google also introduced Antigravity, an agentic IDE powered by Gemini 3 Pro and other models, featuring task orchestration and human-in-the-loop validation. The launch marks Google's strong return to AI with more models expected soon. "Google is very, very back in the business."
OAI and GDM announce IMO Gold-level results with natural language reasoning, no specialized training or tools, under human time limits
gemini-1.5-pro o1 openai google-deepmind reinforcement-learning reasoning model-scaling fine-tuning model-training benchmarking natural-language-processing terence_tao oriol_vinyals alexander_wei jerry_tworek paul_christiano eliezer_yudkowsky
OpenAI and Google DeepMind achieved a major milestone by solving 5 out of 6 problems at the International Mathematical Olympiad (IMO) 2025 within the human time limit of 4.5 hours, earning the IMO Gold medal. This breakthrough was accomplished using general-purpose reinforcement learning and pure in-weights reasoning without specialized tools or internet access, surpassing previous systems like AlphaProof and AlphaGeometry2. The success resolved a 3-year-old AI bet on AI's capability to solve IMO problems and sparked discussions among mathematicians including Terence Tao. Despite this, 26 human competitors remain better than AI on the hardest combinatorics problem (P6). The achievement highlights advances in reinforcement-learning, reasoning, and model-scaling in AI research.