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The world of generative AI continues to evolve rapidly as vendors and researchers race to top one another with new technologies, capabilities and performance milestones.
Large language models (LLMs) are a core element of generative AI, as they are the foundation for building services and applications. OpenAI helped kick off the modern LLM era with its GPT series, and the latest edition — the GPT-4o model — was released on May 13, 2024. GPT-4o offers the promise of multimodality across text, images and audio with more performance at a lower cost than prior GPT-4 releases.
Not to be outdone, Google has been racing to keep up with and possibly outpace OpenAI. In December 2023, Google announced its Gemini multimodal LLM family and has been iterating on it ever since. The Gemini 1.5 Pro model was first announced as a preview in February 2024. The model was publicly demonstrated and expanded significantly at the Google I/O conference in May 2024 alongside the debut of Gemini Flash 1.5.
Gemini 1.5 Pro is a multimodal AI model developed by Google DeepMind to help power generative AI services across Google’s platform and third-party developers.
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Gemini 1.5 Pro is a follow-up release to the initial debut of Google’s Gemini 1.0 in December 2023, which consisted of the Ultra, Pro and Nano models. The first preview of Gemini 1.5 Pro was announced in February 2024, providing an upgrade over the 1.0 models with better performance and longer context length. The initial release was only available in a limited preview to developers and enterprise customers via Google AI Studio and Vertex AI.
In April 2024, Gemini 1.5 Pro was available with a public preview via the Gemini API. At the Google I/O developer conference on May 14, 2024, the vendor announced further improvements to Gemini 1.5 Pro, including quality enhancements across key use cases, such as translation and coding. Gemini 1.5 Pro became generally available on May 23, 2024.
Gemini 1.5 Pro can process text, images, audio and video. This means Gemini 1.5 Pro users and applications can use the model to reason across different modalities to generate text, answer questions and analyze various forms of content.
The Gemini 1.5 Pro model uses an architecture known as a multimodal mixture-of-experts approach. With MoE, Gemini 1.5 Pro can optimize the most relevant expert pathways in its neural network for results. The model handles a large context window of up to 1 million tokens, enabling it to reason and understand larger volumes of data than other models with lower token limits. According to Google, the Gemini 1.5 Pro model delivers comparable results to its older Gemini 1.0 Ultra model with lower computational overhead and cost.
With the Gemini 1.5 Pro update, Google revealed a series of enhancements to the model that included the following:
Gemini 1.5 Pro significantly enhances Google’s capabilities and services with advanced features and improvements for developers and enterprise customers.
Here’s how Gemini 1.5 Pro enhances Google.
Gemini 1.5 Pro’s ability to process and understand text, images, audio and video inputs makes it a versatile tool for enhancing Google’s services. With a context window of up to 2 million tokens, Gemini 1.5 Pro can analyze and understand large amounts of data, which might improve the quality of Google’s search and AI-driven services.
The MoE architecture enables Gemini 1.5 Pro to be more computationally efficient, leading to possible cost savings and faster response times in Google’s cloud and AI services.
Gemini 1.5 Pro is integrated into Google Cloud services, including Vertex AI, enabling developers and businesses to build and deploy AI-driven applications. Google’s services can use Gemini 1.5 Pro to create more intelligent and responsive customer and employee agents.
Gemini 1.5 Pro’s advanced capabilities and efficiency with AI tasks support innovation within Google and among its partners and developers. This can potentially help to encourage and attract an active ecosystem around Google’s AI and cloud platforms.
Gemini 1.5 Pro is a powerful multimodal AI model that can be used for various tasks. Here are some key use cases and capabilities of Gemini 1.5 Pro:
Gemini 1.5 Pro can integrate with several platforms. Platform integration capabilities include the following:
The Gemini 1.5 Pro model was initially available for early testing and private preview in February 2024. It became generally available on May 23, 2024. Gemini 1.5 Pro is available in more than 200 countries and territories through Google AI Studio, Google Vertex AI services and the Gemini API.
Pricing for Gemini 1.5 Pro includes a free and a paid tier.
The free tier has a rate limit of two requests per minute and a total of 50 requests per day. On the paid tier, the rate limit is 1,000 requests per minute. Paid tier pricing is based on token length. For prompts up to 128,000 tokens in size, the price is $1.25 per 1 million tokens, going up to $2.50 per 1 million tokens for prompts longer than 128,000 tokens.
As is the case with other model families, there is a smaller cost-optimized version of Gemini 1.5 Pro: Gemini 1.5 Flash.
Gemini 1.5 Flash is optimized for speed and efficiency. It is intended for high-volume, high-frequency tasks that require rapid processing. However, Gemini 1.5 Flash is not as accurate as Gemini 1.5 Pro. It also does not have access to the 2 million token context window available with Gemini 1.5 Pro.
In October 2024, Google introduced the Gemini 1.5 Flash-8B model, which provides more powerful capabilities than the original Gemini 1.5 Flash at a lower cost.
Editor’s note: This article was updated in January 2025 to reflect new features, functions and pricing.
Sean Michael Kerner is an IT consultant, technology enthusiast and tinkerer. He has pulled Token Ring, configured NetWare and been known to compile his own Linux kernel. He consults with industry and media organizations on technology issues.
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