Google has once again made a big splash in the field of artificial intelligence by officially launching its new large language model, Gemini 3.1 Pro. This release is not just a routine technical iteration but also marks a significant breakthrough in Google's core reasoning capabilities for general artificial intelligence (AGI).

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In terms of version naming, Google broke away from its previous convention of incremental updates in 0.5 steps, and for the first time adopted a ".1" naming approach, emphasizing a qualitative change in the core reasoning architecture. Gemini 3.1 Pro was developed based on a brand-new Core Intelligence architecture, with its research focus entirely on enhancing logical thinking and complex problem-solving capabilities.

According to the latest evaluation data, Gemini 3.1 Pro performed remarkably in the extremely strict ARC-AGI-2 test, achieving an impressive score of 77.1%, which is more than twice the score of its predecessor. In addition, in the so-called "last exam of humanity," the HLE test, it achieved an accuracy rate of 44.4%, successfully surpassing strong competitors GPT-5.2 and Claude Opus 4.6 currently available on the market, setting a new industry record.

In terms of practical application features, Gemini 3.1 Pro demonstrates powerful native multimodal capabilities. It can process ultra-long contexts of up to 1 million Tokens, and it also has strong visual generation and conversion capabilities, directly transforming complex conceptual logic into charts, and even generating SVG animations that can be embedded in web pages. Currently, the model has been officially integrated into the Gemini app and NotebookLM, and developers can also experience it deeply through platforms such as Google AI Studio.

Key Points:

  • 🚀 Significant Improvement in Reasoning Performance: Gemini 3.1 Pro scored more than twice as high in core reasoning tests compared to its predecessor and surpassed GPT-5.2 in the HLE test.

  • 🧠 New Architecture Support: For the first time, it uses a ".1" version name, based on the Core Intelligence architecture, focusing on enhancing the model's logical ability to solve complex problems.

  • 📊 Multimodal and Long Text: Supports context input of up to millions of Tokens and has innovative features that can directly generate charts or SVG animations from complex concepts.