Google Rolls Out Gemini 3.1 Pro With Major Reasoning Improvements

Feb 20, 2026
Google has released Gemini 3.1 Pro, an upgraded large language model with significant improvements in reasoning and benchmark performance. The model is available in preview across developer, enterprise, and consumer platforms.
Google Rolls Out Gemini 3.1 Pro With Major Reasoning Improvements

Google announced in a press release the release of its new Gemini 3.1 Pro model, which introduces major improvements in reasoning and complex task performance. The model achieved a verified score of 77.1% on the ARC-AGI-2 benchmark, more than doubling the reasoning performance of its predecessor.

According to Google, Gemini 3.1 Pro is now available in preview for developers through the Gemini API in AI Studio, Antigravity, and Android Studio. Enterprises can access it via Vertex AI and Gemini Enterprise, while consumers can use it through the Gemini app and NotebookLM, with higher limits for Pro and Ultra plan users.

The model builds on the Gemini 3 series and introduces new capabilities such as generating website-ready animated SVGs directly from text prompts. These code-based animations are designed to maintain quality and small file sizes. Google stated that the preview release will allow continued refinement before a broader general availability rollout.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Daily AI Brief.

Also, consider following us on social media:

AI Brief AI Brief (X)
Free newsletter

Daily AI Brief

Daily report covering major AI developments and industry news, with both top stories and complete market updates

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.