Google Expands Gemini With 3.6 Flash, Flash-Lite and Gemini Robotics 2

Google is expanding Gemini on two fronts at once: faster, lower-cost models for software and enterprise workflows, and a new robotics family designed for embodied, cross-robot control. The releases include Gemini 3.6 Flash , Gemini 3.5 Flash-Lite , Gemini 3.5 Flash Cyber, and Gemini Robotics 2 with related embodied-reasoning and on-device variants. The clearest immediate enterprise story is the widening choice of models for agentic work. In its official Gemini Flash announcement , Google positions 3.6 Flash as a general workhorse for coding, knowledge work, and multimodal tasks, while 3.5 Flash-Lite is aimed at workloads where response speed and cost efficiency are decisive. The robotics update extends the same broader push beyond software agents into systems that must reason about and act in physical environments. A broader Gemini stack for agentic workloads Gemini 3.6 Flash is generally available through Google's developer, enterprise, and consumer channels. Google says it improves on 3.5 Flash for coding, knowledge-work, and multimodal tasks, while producing around 17% fewer output tokens than 3.5 Flash. That token-efficiency claim matters because output tokens are a material part of both latency and inference spending in multi-step agent workflows. Google lists pricing for Gemini 3.6 Flash at $1.50 per 1 million input tokens and $7.50 per 1 million output tokens . The company describes the model as offering a lower cost per task, a metric that depends not only on token prices but also on how many tokens a task requires to complete. The supplied release information does not provide a price for 3.5 Flash-Lite, so it should not be inferred from 3.6 Flash pricing. Gemini 3.5 Flash-Lite occupies a different role. Google calls it its fastest and most cost-effective subfamily, with a stated output speed of 350 output tokens per second . It is intended for high-throughput agentic workflows where an organization may value quick model responses and high request volume ove