Gemini 1.5 Pro explained: Everything you need to know
Explore Google's Gemini 1.5 Pro, a multimodal AI model that offers advanced features, including larger context windows, real-time conversations and expanded Google App extensions.
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.
What is Gemini 1.5 Pro?
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.
What are the enhancements to Gemini?
With the Gemini 1.5 Pro update, Google revealed a series of enhancements to the model that included the following:
- Increased context window. Gemini 1.5 Pro has a context window of 1 million tokens, scalable up to 2 million tokens.
- Improved performance and context understanding. The update offers performance enhancements across various tasks, such as translation, coding and reasoning.
- Enhanced multimodal capabilities. Gemini 1.5 Pro has improved image and video understanding over prior models. It also includes native audio understanding for directly processing voice inputs. The model supports video analysis from linked external sources as well.
- Enhanced function calling and JSON mode. The model can produce JSON objects as structured output from unstructured data, such as images or text. Function calling capabilities have also been enhanced.
- Updated Gemini Advanced. With Gemini Advanced, users can upload files directly from Google Drive for data analysis and custom visualizations.
- Introduced Gems customization. Gemini 1.5 Pro introduces Gems, a feature that lets users create customized versions of the Gemini AI tailored to specific tasks and personal preferences.
- Expanded Google App extensions. Gemini now connects with YouTube Music. Google is rolling out integrations with Google Calendar, Tasks and Keep to enable actions such as creating calendar entries from images.
- Introduced Gemini Live. This new mobile conversational experience offers natural-sounding voices and the ability to interrupt or clarify questions.
How does Gemini 1.5 Pro enhance Google?
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.
Improvements to Google's efficiency
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.
Enhancements to Google's 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.
Competitive advantage
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.
What can Gemini 1.5 Pro be used for?
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:
- Knowledge. Gemini can be used for basic knowledge Q&As based on Google's training data for the base model.
- Summarization. Gemini 1.5 Pro can generate summaries of long-form text, audio recordings or video content.
- Text content generation. The language understanding and generation capabilities of Gemini 1.5 Pro can be used for tasks such as story writing, content creation and scriptwriting.
- Multimodal question answering. Gemini 1.5 Pro can combine information from text, images, audio and video to answer questions spanning multiple modalities.
- Long-form content analysis. With its large context window of up to 2 million tokens, Gemini 1.5 Pro surpasses previous Gemini models in its ability to analyze and understand lengthy documents, books, codebases and videos.
- Visual information analysis. The model can generate descriptions or explanations related to the visual content.
- Translation. Users can translate between languages with this model.
- Intelligent assistants and chatbots. Gemini 1.5 Pro can be used to build conversational AI assistants that can understand and reason over multimodal inputs.
- Code analysis and generation. Gemini 1.5 Pro understands application development code. The model can analyze entire codebases, suggest improvements, explain code functionality and generate new code snippets.
- Audio processing. As part of its multimodal capabilities, Gemini 1.5 Pro can process and analyze complex audio inputs, including multispeaker conversations.
Gemini 1.5 Pro integration with other platforms
Gemini 1.5 Pro can integrate with several platforms. Platform integration capabilities include the following:
- Vertex AI. Gemini 1.5 Pro is integrated into Google Cloud's Vertex AI platform, enabling developers to build, deploy and manage AI models.
- AI Studio. Developers can access Gemini 1.5 Pro through Google AI Studio, a web-based tool for prototyping and running prompts directly in the browser.
- Gemini API. The Gemini API lets developers integrate Gemini 1.5 Pro into their applications or platforms. This includes generating content, analyzing data and solving problems using text, images, audio and video inputs.
- JSON mode and function calling. The API supports JSON mode for structured data extraction and enhanced function calling capabilities, making it easier to integrate with other systems and applications.
- Google Workspace. Gemini 1.5 Pro is integrated into Google Workspace, including Gmail, Docs and other Google apps.
- Mobile apps. Developers can integrate Gemini 1.5 Pro into mobile applications using APIs and SDKs.
- Web applications. The Gemini API can integrate AI capabilities into web applications, enabling features such as chatbots, content generation and data analysis.
Gemini 1.5 Pro availability and costs
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.
Comparing Gemini 1.5 Pro vs. Gemini 1.5 Flash
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.
| Feature | Gemini 1.5 Pro | Gemini 1.5 Flash | Gemini 1.5 Flash-8B |
| Capabilities | Complex reasoning, advanced AI projects | High-volume, rapid processing | High-volume, rapid processing |
| Context window | Up to 2 million tokens | Up to 1 million tokens | Up to 1 million tokens |
| Output type | Text | Text | Text |
| Use cases | Long-form content analysis, advanced code generation and detailed multimodal Q&A | Summarization, chat, image and video captioning, and data extraction | Basic text processing, simple queries and lightweight applications |
| Pay-as-you-go rate limits | 1,000 requests per minute, 4 million tokens per minute | 2,000 requests per minute, 4 million tokens per minute | 4,000 requests per minute, 4 million tokens per minute |
| Input pricing (up to 128,000 tokens) | $1.25 per 1 million tokens | $0.075 per 1 million tokens | $0.0375 per 1 million tokens |
| Input pricing (longer than 128,000 tokens) | $2.50 per 1 million tokens | $0.15 per 1 million tokens | $0.075 per 1 million tokens |
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.
