Google announced the release of its latest frontier model, Gemini 3.1 Pro, on Thursday during the AI Impact Summit 2026. Positioned as the most advanced reasoning model in the Gemini 3 series, it aims to reclaim the AI throne from Anthropic’s Claude 4.6 and OpenAI’s GPT-5.2.
The update focuses on “core intelligence,” specifically targeting complex problem-solving in science, research, and engineering. While its predecessor was a “multimodal powerhouse,” the 3.1 Pro iteration adds a layer of deep logical reasoning that allows it to solve unfamiliar tasks that were previously impossible for LLMs.
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The Intelligence Index Leaderboard
In the latest Artificial Analysis Intelligence Index, Gemini 3.1 Pro scored a 57, placing it four points ahead of Claude Opus 4.6. This index serves as a global standard for intelligence, speed, and pricing.
More impressively, the model achieved this while being significantly more efficient. It required 57 million tokens to complete the evaluation, far lower than the token verbosity of GPT-5.2. For developers, this translates to a model that is not only “smarter” but also roughly 50% cheaper to operate in high-volume production environments.
Reasoning & Coding: SciCode and Terminal-Bench
The model’s standout performance is found in the ARC-AGI-2 benchmark, which tests a model’s ability to learn new logic patterns on the fly. Gemini 3.1 Pro scored 77.1%, nearly a 24% lead over GPT-5.2.
In specialized coding, the model holds the top scores in:
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SciCode: 59% (Scientific research programming).
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Terminal-Bench Hard: 54% (Agentic terminal use and command-line execution).
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LiveCodeBench Pro: 2887 Elo points (Competitive programming).
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New “Agentic” Capabilities & Animated SVGs
One of the most practical additions is the model’s ability to generate animated SVGs directly from text prompts. Unlike traditional video, these are pure code, meaning they remain sharp at any resolution and are incredibly lightweight for web applications.
Furthermore, Gemini 3.1 Pro features a “Medium Thinking” level. This allows users to choose between a fast, direct response or a deeper, multi-step reasoning process for harder problems. It retains its industry-leading 1 million token context window, now optimized for tool orchestration and JSON mode for enterprise developers.
Reality Check
Google claims 3.1 Pro “defeats” the competition. Still, in real-world expert tasks measured by GDPval-AA, it still trails behind Claude Sonnet 4.6 and Opus 4.6. Therefore, while Gemini wins in “academic” and “logic” puzzles, Anthropic’s models remain the preferred choice for long-horizon agentic workflows and consistent expert reasoning. In fact, many developers find that Gemini’s “verbosity” can lead to higher total costs despite the lower per-token price.
The Loopholes
The 3.1 Pro update includes a 38-point reduction in the AA-Omniscience hallucination rate. In fact, this is compared to the “Gemini 3 Pro Preview” from late 2025 rather than the finalized 3.0 Pro. Therefore, the “leap” appears larger because it’s measured against an experimental version. Still, the ARC-AGI-2 score is verified, meaning the reasoning jump is a genuine hardware and algorithmic breakthrough rather than a statistical loophole
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What This Means for You
If you are a developer, 3.1 Pro is now the most cost-effective “Thinking” model for your API stack. First, switch your endpoints to gemini-3.1-pro-preview in Google AI Studio to benefit from the lower token costs. Then, explore the “Thought Signatures” in the multi-turn tool calling; this is required to keep the model’s reasoning consistent during long agentic tasks.
Finally, realize that NotebookLM users on Pro and Ultra plans now have exclusive access to this model for synthesizing long research papers. You should use the new SVG generation feature for your web mockups to save on design assets. Before the general availability, expect higher rate limits if you are already on the Gemini Enterprise plan via Vertex AI.
What’s Next
Gemini 3.1 Pro began its global rollout on February 19, 2026. Then, we expect a public “Agentic Update” in March that will allow the model to autonomously browse and execute local code via Google Antigravity. Finally, the first integration with Android Studio for on-device 3.1 Pro inference is scheduled for late April.
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