Best AI Models for Gemma
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Compare the Top AI Models that integrate with Gemma as of November 2025
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This a list of AI Models that integrate with Gemma. Use the filters on the left to add additional filters for products that have integrations with Gemma. View the products that work with Gemma in the table below.
What are AI Models for Gemma?
AI models are systems designed to simulate human intelligence by learning from data and solving complex tasks. They include specialized types like Large Language Models (LLMs) for text generation, image models for visual recognition and editing, and video models for processing and analyzing dynamic content. These models power applications such as chatbots, facial recognition, video summarization, and personalized recommendations. Their capabilities rely on advanced algorithms, extensive training datasets, and robust computational resources. AI models are transforming industries by automating processes, enhancing decision-making, and enabling creative innovations. Compare and read user reviews of the best AI Models for Gemma currently available using the table below. This list is updated regularly.
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1
Vertex AI
Google
AI Models in Vertex AI offer businesses access to pre-trained and customizable models for a variety of use cases, from natural language processing to image recognition. These models are powered by the latest advancements in machine learning and can be tailored to meet specific business requirements. By offering flexible model-building and deployment tools, Vertex AI enables businesses to integrate AI into their operations seamlessly. New customers receive $300 in free credits, allowing them to explore different AI models and experiment with adapting them to their specific needs. Vertex AI’s extensive catalog of models provides a foundation for businesses to implement cutting-edge AI solutions and drive innovation.Starting Price: Free ($300 in free credits) -
2
Google AI Studio
Google
Google AI Studio provides a wide range of pre-built AI models that users can leverage for various applications, from natural language processing to image recognition. These models are designed to be flexible and adaptable, allowing businesses to integrate AI capabilities into their systems with minimal setup. The platform offers both general-purpose models for common tasks as well as specialized models for more advanced use cases, such as sentiment analysis or predictive maintenance. Furthermore, Google AI Studio allows users to customize and fine-tune these models to meet specific business needs, making it easier to deploy AI solutions that are both accurate and scalable.Starting Price: Free -
3
Gemma 3n
Google DeepMind
Gemma 3n is our state-of-the-art open multimodal model, engineered for on-device performance and efficiency. Made for responsive, low-footprint local inference, Gemma 3n empowers a new wave of intelligent, on-the-go applications. It analyzes and responds to combined images and text, with video and audio coming soon. Build intelligent, interactive features that put user privacy first and work reliably offline. Mobile-first architecture, with a significantly reduced memory footprint. Co-designed by Google's mobile hardware teams and industry leaders. 4B active memory footprint with the ability to create submodels for quality-latency tradeoffs. Gemma 3n is our first open model built on this groundbreaking, shared architecture, allowing developers to begin experimenting with this technology today in an early preview. -
4
Gemma 2
Google
A family of state-of-the-art, light-open models created from the same research and technology that were used to create Gemini models. These models incorporate comprehensive security measures and help ensure responsible and reliable AI solutions through selected data sets and rigorous adjustments. Gemma models achieve exceptional comparative results in their 2B, 7B, 9B, and 27B sizes, even outperforming some larger open models. With Keras 3.0, enjoy seamless compatibility with JAX, TensorFlow, and PyTorch, allowing you to effortlessly choose and change frameworks based on task. Redesigned to deliver outstanding performance and unmatched efficiency, Gemma 2 is optimized for incredibly fast inference on various hardware. The Gemma family of models offers different models that are optimized for specific use cases and adapt to your needs. Gemma models are large text-to-text lightweight language models with a decoder, trained in a huge set of text data, code, and mathematical content. -
5
PaliGemma 2
Google
PaliGemma 2, the next evolution in tunable vision-language models, builds upon the performant Gemma 2 models, adding the power of vision and making it easier than ever to fine-tune for exceptional performance. With PaliGemma 2, these models can see, understand, and interact with visual input, opening up a world of new possibilities. It offers scalable performance with multiple model sizes (3B, 10B, 28B parameters) and resolutions (224px, 448px, 896px). PaliGemma 2 generates detailed, contextually relevant captions for images, going beyond simple object identification to describe actions, emotions, and the overall narrative of the scene. Our research demonstrates leading performance in chemical formula recognition, music score recognition, spatial reasoning, and chest X-ray report generation, as detailed in the technical report. Upgrading to PaliGemma 2 is a breeze for existing PaliGemma users. -
6
Gemini Robotics
Google DeepMind
Gemini Robotics brings Gemini’s capacity for multimodal reasoning and world understanding into the physical world, allowing robots of any shape and size to perform a wide range of real-world tasks. Built on Gemini 2.0, it augments advanced vision-language-action models with the ability to reason about physical spaces, generalize to novel situations, including unseen objects, diverse instructions, and new environments, and understand and respond to everyday conversational commands while adapting to sudden changes in instructions or surroundings without further input. Its dexterity module enables complex tasks requiring fine motor skills and precise manipulation, such as folding origami, packing lunch boxes, or preparing salads, and it supports multiple embodiments, from bi-arm platforms like ALOHA 2 to humanoid robots such as Apptronik’s Apollo. It is optimized for local execution and has an SDK for seamless adaptation to new tasks and environments.
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