Google Gemini 3.1 Pro debuts with massive reasoning leap

Google says it is releasing Gemini 3.1 Pro, describing it as the “upgraded core intelligence” behind a recent Gemini 3 Deep Think update and positioning it as a smarter baseline for “tasks where a simple answer isn’t enough.”

Gemini 3.1 Pro is rolling out starting today across multiple products:

• Developers (preview): Gemini API via Google AI Studio, Gemini CLI, Google Antigravity, and Android Studio
• Enterprises: Vertex AI and Gemini Enterprise
• Consumers: the Gemini app and NotebookLM

Google highlights an ARC-AGI-2 “verified” score of 77.1%

Google’s headline performance claim for Gemini 3.1 Pro is its progress on ARC-AGI-2, which Google describes as a benchmark that evaluates a model’s ability to solve entirely new logic patterns. Google says Gemini 3.1 Pro achieved a verified score of 77.1% on ARC-AGI-2 and calls that “more than double” the reasoning performance of Gemini 3 Pro.

For reference, Google DeepMind’s official Gemini 3 Pro benchmark table lists 31.1% for ARC-AGI-2 (ARC Prize Verified) for Gemini 3 Pro.

What Google says Gemini 3.1 Pro is meant to do

Google frames Gemini 3.1 Pro as a model aimed at applying advanced reasoning to real workflows, such as:

• generating website-ready animated SVGs from a prompt,
• building a live dashboard that visualizes an International Space Station telemetry stream,
• producing interactive, code-driven experiences (Google’s example: a 3D starling murmuration).

Availability details and plan limits

Google says Gemini 3.1 Pro is launching in preview as it validates updates before making it “generally available soon.” On the consumer side, Google adds that Gemini 3.1 Pro in the Gemini app is rolling out with higher limits for users on the Google AI Pro and Ultra plans, while NotebookLM access is listed as exclusive to Pro and Ultra users.

What we still can’t confirm from Google’s post alone

Google’s post focuses on rollout and benchmark highlights, but it doesn’t include a full spec sheet with details like pricing, country-by-country availability, or exact API model names. For those specifics, Google points developers and businesses to the official Gemini API and Vertex AI documentation.