What is Gemini 3.1 Pro?

Gemini 3.1 Pro is Google DeepMind's current flagship reasoning model, and its benchmark trajectory tells an unusual story: a mid-cycle update, released in preview on February 19, 2026, that outpaced its own predecessor by a wider margin than most full-generation releases. Built on the Gemini 3 Pro architecture rather than a ground-up redesign, it concentrates gains on reasoning depth while preserving the same multimodal and long-context foundation.[1] The model accepts text, images, audio, video

Why did Gemini 3.1 Pro's release matter so quickly?

The Gemini 2.5 Pro had a well-documented asymmetry: strong on multimodal and long-context grounded tasks, weak on abstract reasoning and complex agentic coding. Its 4.9% score on ARC-AGI-2 - the ARC Prize's benchmark for novel rule-induction specifically designed to defeat memorization - was not a competitive number at launch, and it did not improve over the model's operational life. Gemini 3.1 Pro scores 77.1% on the same test, independently verified by the ARC Prize.[1] That is not iteration.

How does Gemini 3.1 Pro compare to Claude Opus 4.6 and GPT-5.4?

The table below draws primarily from the official Gemini 3.1 Pro model card and the Artificial Analysis independent benchmark leaderboard, with GPT-5.4 figures cross-referenced against the OpenAI launch announcement.[1][5][6] GPT-5.4 launched on March 5, 2026; figures reflect standard (non-Pro) variants throughout for consistency, except where noted.A note on benchmark sourcing: Where Artificial Analysis has independently run an evaluation, those figures are marked (AA) and should be treated as

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AI Research

Vol. 1·Friday, April 3, 2026

Gemini 3.1 Pro Reviewed: Google's Reasoning Reversal

Noah OgbiUpdated Apr 5, 2026

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AI Research

Vol. 1·Saturday, March 28, 2026

Google's TurboQuant Compresses AI Memory by 6x. Wall Street Panicked.

Google Research has published TurboQuant, an algorithm that cuts the memory cost of running large AI models by at least sixfold - with no accuracy penalty and no retraining required. Memory chip stocks sold off sharply. The sell-off misread what the research actually says.

Noah Ogbi

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Vol. 1·Tuesday, March 24, 2026

Runway and NVIDIA Collapse the Gap Between Thought and Video

A research preview unveiled at NVIDIA GTC shows HD video generated in under 100 milliseconds, a latency drop so sharp it changes what video AI is, not just how fast it runs. The creative and safety implications are profound.

Noah Ogbi

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AI Research

Vol. 1·Monday, March 23, 2026

Companies Are Spending the Most on AI Where It Works the Least

Global AI spending is on track to hit $2.52 trillion in 2026, yet 95% of task-specific enterprise AI deployments deliver zero measurable P&L impact. The problem isn't the technology - it's where the money is going.

Noah Ogbi

MITGenAI

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