Google's AI landscape just got a major upgrade with the introduction of Gemini 2.0, a suite of models designed to improve both developer and user experiences.
Here's a breakdown of what's new:
This model is Google's most cost-efficient yet, with improved performance over its predecessors while maintaining speed and affordability.
It's good at handling tasks with a context window of up to 1 million tokens, making it good for high-volume applications.
Now generally available, this model is optimized for high-frequency tasks and excels in multimodal reasoning, processing vast amounts of information efficiently.
Developers can access it via the Gemini API in Google AI Studio and Vertex AI.
Tailored for complex tasks, this experimental model offers enhanced coding performance and better handling of intricate prompts.
It features an expanded context window of 2 million tokens and the ability to utilize tools like Google Search and code execution.
Currently, it's available to developers and Gemini Advanced users.
In addition to these models, Google has introduced the “Flash Thinking” experimental feature in the Gemini app.
This reasoning AI model is capable of explaining complex questions and interacting with applications like YouTube and Google Maps, providing users with more intuitive and informative responses.
These developments are part of Google's broader strategy to advance AI capabilities while addressing cost concerns in the industry.
The introduction of more efficient models like Flash-Lite is part of a commitment to making AI more accessible and practical for a wide range of applications.
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