"Measured by the release cadence of machine learning models, Gemini 3.1 Pro is hard on the heels of recent model debuts from Anthropic and OpenAI. There's barely enough time to start using new US commercial AI models before a competitive alternative surfaces. And that's to say nothing about the AI models coming from outside the US, like Qwen3.5."
"On the ARC-AGI-2 problem-solving test, Gemini 3.1 Pro scored 77.1 percent, compared to Gemini 3 Pro, which scored 31.1 percent, and Gemini 3 Deep Think, which scored 45.1 percent. Gemini 3.1 Pro outscores rival commercial models like Anthropic's Opus 4.6 and Sonnet 4.6, and OpenAI's GPT-5.2 and GPT-5.3-Codex in the majority of cited benchmarks, Google's chart shows. However, Opus 4.6 retains the top score for Humanity's Last Exam (full set, test + MM), SWE-Bench Verified, and τ²-bench. And GPT-5.3-Codex leads in SWE-Bench Pro (Public) and Terminal-Bench 2.0 when evaluated using Codex's own harness rather than the standard Terminus-2 agent harness."
Google released Gemini 3.1 Pro, a model targeted at improved core reasoning and complex problem solving. The model achieved a 77.1 percent score on the ARC-AGI-2 problem-solving test, compared with Gemini 3 Pro at 31.1 percent and Gemini 3 Deep Think at 45.1 percent. Google presented comparisons showing Gemini 3.1 Pro outperforming several commercial rivals across many benchmarks, though competitors like Anthropic's Opus 4.6 and OpenAI's GPT-5.3-Codex keep top placements on specific tests. Gemini 3.1 Pro is positioned for practical applications such as creating visual explanations, synthesizing data views, and generating website-ready SVG animations.
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