Google is releasing a new AI model designed to deliver strong performance with a focus on efficiency.
The model, Gemini 2.5 Flash, will soon launch in Vertex AI, Google’s AI development platform. The company says it offers “dynamic and controllable” computing, allowing developers to adjust processing time based on the complexity of queries.
“[You can tune] the speed, accuracy, and cost balance for your specific needs,” Google wrote in a blog post provided to TechCrunch. “This flexibility is key to optimizing Flash performance in high-volume, cost-sensitive applications.”
Gemini 2.5 Flash arrives as the cost of flagship AI models continues trending upward. Lower-priced, performant models like 2.5 Flash present an attractive alternative to costly top-of-the-line options at the cost of some accuracy.
Gemini 2.5 Flash is a “reasoning” model along the lines of OpenAI’s o3-mini and DeepSeek’s R1. That means it takes a bit longer to answer questions in order to fact-check itself.
Google says that 2.5 Flash is ideal for “high-volume” and “real-time” applications like customer service and document parsing.
“This workhorse model is optimized specifically for low latency and reduced cost,” Google said in its blog post. “It’s the ideal engine for responsive virtual assistants and real-time summarization tools where efficiency at scale is key.”
Google didn’t publish a safety or technical report for Gemini 2.5 Flash, making it more challenging to see where the model excels and falls short. The company previously told TechCrunch that it doesn’t release reports for models it considers to be “experimental.”
Google also announced on Wednesday that it plans to bring Gemini models like 2.5 Flash to on-premises environments starting in Q3. The company’s Gemini models will be available on Google Distributed Cloud (GDC), Google’s on-prem solution for clients with strict data governance requirements. Google says it’s working with Nvidia to bring Gemini models to GDC-compliant Nvidia Blackwell systems that customers can purchase through Google or their preferred channels.
Kyle Wiggers is TechCrunch’s AI Editor. His writing has appeared in VentureBeat and Digital Trends, as well as a range of gadget blogs including Android Police, Android Authority, Droid-Life, and XDA-Developers. He lives in Manhattan with his partner, a music therapist.
