Google unveils Gemini 3.7 Flash AI model for coding, agent workflows

Alphabet's Google unveiled Gemini 3.7 Flash on Thursday, its newest AI model tailored for software coding and automated business processes, though the company did not disclose when its premium Pro model will be released. Investors have been monitoring Gemini 3.5 Pro, Google's premium model, as a benchmark for the potential performance of its DeepMind AI unit against competitors Anthropic and OpenAI.

In July, Google stated that Gemini 3.5 Pro was being piloted with partners and would arrive "soon." The company markets Gemini 3.7 Flash as a cost-effective solution for businesses aiming to develop autonomous AI systems capable of planning tasks, utilizing software tools, and executing multi-step workflows with minimal human involvement.

The model was launched three weeks after Gemini 3.6 Flash and has demonstrated improved performance in coding tasks such as debugging, problem-solving, and generating production-ready code, as reported by Google's blog post. To encourage adoption, Google is offering Gemini 3.7 Flash at a discounted rate of 75 cents per million input tokens and $3.75 per million output tokens through the end of the year, which is half the original price of Gemini 3.6 Flash.

The model has been immediately deployed to Gemini Spark, Google's subscription-based AI agent service available to Google AI Pro and Ultra customers across more than 160 countries. Google co-founder Sergey Brin has recently encouraged top AI personnel to focus solely on the Gemini model as Alphabet strives to narrow the gap with its rivals, according to Reuters.

Earlier this week, the tech giant announced a major leadership reshuffle within its Google DeepMind AI division, with its chief Demis Hassabis handing over the reins to his deputy Koray Kavukcuoglu. Simultaneously, the two founding technical co-leads of Gemini departed to establish a new startup. During Google's July earnings call, CEO Sundar Pichai staunchly defended the company's AI strategy, addressing concerns about falling behind rivals due to delayed model release and losing ground in AI coding.