Google launches Gemini 3.1 Pro with major AI reasoning upgrade

Gemini 3.1 Pro delivers more than double the reasoning performance of its predecessor, keeps the same pricing, and rolls out in preview across multiple Google platforms.

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Summary

Google has released Gemini 3.1 Pro, the first “.1” update in the Gemini series, with a major jump in reasoning capabilities over Gemini 3 Pro. The model scores 77.1% on the ARC-AGI-2 benchmark, up from 31.1%, and now leads six out of ten evaluations in Artificial Analysis’s Intelligence Index.

The company says the model brings reasoning improvements from Gemini 3 Deep Think into a more accessible package for developers and everyday users. Despite the performance boost, pricing remains unchanged at 2 dollars per million input tokens and 12 dollars per million output tokens.

Artificial Analysis reports that Gemini 3.1 Pro costs less than half as much as rival frontier models to run comparable benchmark tests. The launch clearly aims to strengthen Google’s position in the AI race against competitors such as OpenAI and Anthropic.

In practice

Gemini 3.1 Pro is rolling out in preview through the Gemini API in Google AI Studio, the Gemini CLI, the agentic development platform Google Antigravity, and Android Studio. Enterprise customers can access the model via Vertex AI and Gemini Enterprise.

For consumers, the model is available in the Gemini app for Google AI Pro and Ultra subscribers, who also benefit from higher usage limits. NotebookLM also adopts Gemini 3.1 Pro, but access is reserved for Pro and Ultra subscribers.

Google highlights use cases such as “complex system synthesis”, where the model connects advanced APIs to user-friendly interfaces. In one demonstration, Gemini 3.1 Pro built a live aerospace dashboard tracking the International Space Station’s orbit and generated animated SVG graphics from text prompts, producing code-based visualizations instead of pixel images.

Context

Gemini 3.1 Pro arrives at a time when leading AI models are competing heavily on reasoning strength and cost per use. By pairing a leap in logic benchmarks with stable pricing, Google is targeting technical and business teams that already rely on AI in their daily work.

The preview rollout allows the model to be tested across products before wider availability. Google says further enhancements are planned for agentic workflows, where the model coordinates complex tasks that involve multiple tools and steps.

Why it matters

Gives organisations stronger AI reasoning without raising per-token costs.
Makes it easier to build dashboards, API integrations, and visualisations directly from text.
Intensifies competition among frontier AI models, potentially helping prices and innovation.
Can make tools like the Gemini app and NotebookLM more useful for power users.