Broad range of applications
Deliver relevant search results
Built-in support for responsible AI
Meet Amazon Titan
Exclusive to Amazon Bedrock, the Amazon Titan family of models incorporates Amazon’s 25 years of experience innovating with AI and machine learning across its business. Amazon Titan foundation models (FMs) provide customers with a breadth of high-performing image, multimodal, and text model choices, via a fully managed API. Amazon Titan models are created by AWS and pretrained on large datasets, making them powerful, general-purpose models built to support a variety of use cases, while also supporting the responsible use of AI. Use them as is or privately customize them with your own data.
Use Titan Text models to improve productivity and efficiency for an extensive range of text-related tasks, such as creating copy for blog posts and web pages, classifying articles into categories, open-ended Q&A, conversational chat, information extraction, and more.
Use Titan Text models to get concise summaries of long documents such as articles, reports, research papers, technical documentation, and more to quickly and effectively extract important information.
Use Titan Multimodal Embeddings and Titan Text Embeddings to power more accurate and contextually relevant multimodal search, recommendation, and personalization experiences for end users.
Enable content creators with rapid ideation and iteration resulting in high efficiency image generation. Customers in industries like advertising, e-commerce, and media and entertainment can generate realistic, studio-quality images in large volumes and at low cost, using natural language prompts.
Retrieval Augmented Generation (RAG)
Deliver more up-to-date and accurate results for user queries by connecting FMs to your data sources. Extend the already powerful capabilities of Titan models and make them more knowledgeable about your specific domain and organization.
Titan Text Express
LLM offering a balance of price and performance.
Max tokens: 8K
Languages: English (GA), 100+ languages available (Preview)
Fine-tuning supported: Yes
Supported use cases: Retrieval augmented generation, open-ended text generation, brainstorming, summarization, code generation, table creation, data formatting, paraphrasing, chain of thought, rewrite, extraction, Q&A,
Titan Text Embeddings
LLM that translates text into numerical representations.
Max tokens: 8K
Languages: 25+ languages
Fine-tuning supported: No
Supported use cases: Text retrieval, semantic similarity, and clustering.
Titan Multimodal Embeddings
Powers accurate multimodal search and recommendation experiences.
Max tokens: 128
Max images size: 25 MB
Fine-tuning supported: Yes
Embeddings: 1,024 (default), 384, 256
Supported use cases: Search, recommendation, personalization
Titan Image Generator (preview)
Amazon Titan Image Generator features
Amazon Titan Image Generator enables content creators with rapid ideation and iteration resulting in high efficiency image generation. You can edit your generated or existing images using text prompts, configure image dimensions, or specify the number of image variations you want the model to generate. You can also securely customize this model using your company data to produce images consistent with your brand style.
Text to image
Generate high-quality, realistic images using natural-language prompts.
Prompt: “green iguana”
Securely customize this model using company data to produce images consistent with your brand style. For example, adapt the realistic iguana into a cartoon or a sketch.
Prompt: “iguana as a cartoon”
Prompt: “iguana as a sketch”
Edit an existing or generated image with a text prompt. No image mask needed.
Input: Image + “iguana in a rain forest” as a prompt
Edit parts of an image to remove or replace certain objects with a mask area you define.
Input: Image + a mask area of the iguana + “toucan” as a prompt
Replace an existing background to generate lifestyle images with a mask area you define.
Input: Image + a mask area of the background + “beach” as a prompt
Extend an image’s borders with additional details while retaining the main subject of the image. For example, extend the tail of the iguana.
Input: Image + a mask area with the new borders + “iguana tail” as a prompt
Create multiple variants of an image, guided by an optional text prompt.
Prompt: “a green iguana in a rainforest”