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Alphabet's Google launched Gemini 3.7 Flash on Thursday, its latest AI model designed for software coding and automated business tasks, but offered no details on when its flagship Pro model will be released.
Investors have been closely watching for Gemini 3.5 Pro, Google's premium model, as a test of whether its DeepMind AI unit can keep pace with rivals Anthropic and OpenAI.
Google had said in July Gemini 3.5 Pro was being tested with partners and would be coming "soon".
Here are a few details on Gemini 3.7 Flash:
- The company is pitching the model as a lower-cost option for businesses building autonomous AI systems that can plan tasks, use software tools and complete multi-step workflows with less human intervention.
- Gemini 3.7 Flash is released three weeks after Gemini 3.6 Flash. It has shown improved performance on coding tasks, including debugging, issue resolution and production-ready code generation, according to a Google blog post.
- To drive adoption, Google is offering Gemini 3.7 Flash at an introductory rate of 75 cents per million input tokens and $3.75 per million output tokens through the end of the year, half the original cost of Gemini 3.6 Flash.
- The model is also being rolled out immediately to Gemini Spark, Google's subscription-based AI agent service available to Google AI Pro and Ultra customers in more than 160 countries.
- Google co-founder Sergey Brin in recent months has urged key AI staff to go all in on the company's Gemini model as parent Alphabet seeks to close the gap with rivals, Reuters exclusively reported on Wednesday.
- Last week, the tech giant announced a sweeping leadership overhaul of its Google DeepMind AI division in which its chief, Demis Hassabis, stepped aside in favor of his deputy, Koray Kavukcuoglu. At the same time, the two original technical co-leads of Gemini quit to co-found a startup.
- CEO Sundar Pichai mounted a robust defense of Google's AI strategy during its earnings call in July, pushing back on concerns that the company has fallen behind rivals after delaying the flagship model and ceding ground in AI coding.
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