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

Alphabet's Google introduced Gemini 3.7 Flash on Thursday, an AI model specifically designed for software coding and automated business processes. However, the company did not provide an estimated release date for its flagship Gemini 3.5 Pro model. Investors have been eagerly anticipating Gemini 3.5 Pro as a benchmark to gauge Google's DeepMind AI unit's competitiveness against Anthropic and OpenAI.

Gemini 3.7 Flash is positioned as a more cost-effective solution for businesses aiming to create autonomous AI systems capable of planning tasks, utilizing software tools, and executing multi-step workflows with minimal human oversight. The model debuted three weeks after its predecessor, Gemini 3.6 Flash, and has demonstrated enhanced performance in coding tasks, such as debugging, issue resolution, and generating production-ready code.

To encourage wider adoption, Google has set an introductory pricing structure for Gemini 3.7 Flash, offering the service at $0.75 per million input tokens and $3.75 per million output tokens through the end of the year. This rate is half the original cost of Gemini 3.6 Flash. Moreover, the model has been immediately made available to Gemini Spark, Google's subscription-based AI agent service, which is accessible to Google AI Pro and Ultra customers in over 160 countries.

Google co-founder Sergey Brin has been advocating for a strong focus on the Gemini model as Alphabet strives to narrow the gap with its competitors. In recent months, Brin made his appeal to key AI staff, as reported exclusively by Reuters. Additionally, Google recently announced a significant leadership transition within its Google DeepMind AI division, with its chief, Demis Hassabis, stepping down to be replaced by his deputy, Koray Kavukcuoglu.

Notably, two original technical co-leads of Gemini recently left the company to establish a startup.

CEO Sundar Pichai defended Google's AI strategy during the company's July earnings call, addressing concerns about falling behind rivals due to the delayed release of the flagship model and losing ground in AI coding.