ust a few months after Gemini 3 shook the industry, Google’s back with another upgrade to its flagship model – and it runs cheaper than rival Anthropic's cutting-edge model.
On Thursday, Google unveiled the preview of Gemini 3.1 Pro, the latest iteration in the Gemini series. Google’s model beats out Anthropic’s Claude and OpenAI’s GPT models in benchmarks related to reasoning, scientific knowledge, agentic terminal coding and tool use, and long-horizon professional tasks.
Gemini 3.1 Pro can handle multimodal inputs, including text, images, audio, and video files, with a context window of up to 1 million tokens. Its outputs, meanwhile, are text-based and up to 64,000 tokens. In a post on X, Google called Gemini 3.1 Pro its “new baseline for complex problem solving.”
The big news? Google’s model offers frontier capabilities at a lower cost than recent releases from rivals:
- Gemini 3.1 Pro costs $2 per one million token input and $12 per $2 per one million token output.
- Meanwhile, Claude Opus 4.6, Anthropic’s recently-released update to its flagship model, costs roughly $5 per million-token input and $25 per million-token output. It also undercuts Sonnet 4.6, Anthropic’s faster, mid-tier model, which sits at $3 per million-token input and $12 per million-token output.
- Google’s latest model is competitively priced with OpenAI’s GPT-5.2, which costs slightly less at $1.75 per million-token input and slightly more at $14 per million-token output.
Currently, Gemini 3.1 Pro is available in the Gemini app and NotebookLM for users with Google AI Pro and Ultra Plans. For developers, the model is now available via its suite of enterprise apps, including AI Studio, Antigravity, Vertex AI, Gemini Enterprise, Gemini CLI and Android Studio.
Our Deeper View
Google might shake out to be one of the biggest winners of the AI war, and not just because its models continue to break benchmarks. Though the Anthropic versus OpenAI rivalry is taking up a good deal of airtime, Google’s legacy in both the consumer and enterprise spaces gives it a foundation to better serve a larger number of users. Plus, if it’s able to undercut competitors at a time when AI costs are becoming stifling, Google not only has the opportunity to make models more accessible and democratized, but also to foster long-term progress. After all, decreasing cost curves tends to be one of the most powerful, although less flashy, ways to move the needle on innovation.