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Amazon Bedrock

Meta's Llama in Amazon Bedrock

Build the future of AI with Llama

Get started with Llama in Amazon Bedrock

Introducing Llama 3.3

Llama 3.3 is a text-only 70B instruction-tuned model that provides enhanced performance relative to Llama 3.1 70B–and to Llama 3.2 90B when used for text-only applications. Llama 3.3 70B delivers similar performance to Llama 3.1 405B, while requiring only a fraction of the computational resources.

Llama 3.3 70B’s comprehensive training results in robust understanding and generation capabilities across diverse tasks. This model supports high-performance conversational AI designed for content creation, enterprise applications, and research, offering advanced language understanding capabilities, including text summarization, classification, sentiment analysis, and code generation.

Llama 3.2 90B is Meta’s most advanced model and is ideal for enterprise-level applications. Llama 3.2 is the first Llama model to support vision tasks, with a new model architecture that integrates image encoder representations into the language model. This model excels at general knowledge, long-form text generation, multilingual translation, coding, math, and advanced reasoning. It also introduces image reasoning capabilities, allowing for sophisticated image understanding and visual reasoning. This model is ideal for the following use cases: image captioning, image-text-retrieval, visual grounding, visual question answering and visual reasoning, and document visual question answering.

Llama 3.2 11B is well-suited for content creation, conversational AI, language understanding, and enterprise applications requiring visual reasoning. The model demonstrates strong performance in text summarization, sentiment analysis, code generation, and following instructions, with the added ability to reason about images. This model is ideal for the following use cases: image captioning, image-text-retrieval, visual grounding, visual question answering and visual reasoning, and document visual question answering.

Llama 3.2 3B offers a more personalized AI experience, with on-device processing. Llama 3.2 3B is designed for applications requiring low-latency inferencing and limited computational resources. It excels at text summarization, classification, and language translation tasks. This model is ideal for the following use cases: mobile AI-powered writing assistants and customer service applications.

Llama 3.2 1B is the most lightweight model in the Llama 3.2 collection of models and is perfect for retrieval and summarization for edge devices and mobile applications. It enables on-device AI capabilities while preserving user privacy and minimizing latency. This model is ideal for the following use cases: personal information management and multilingual knowledge retrieval.

Benefits

LOREM IPSUM

Llama 3.2 offers a more personalized AI experience, with on-device processing. The Llama 3.2 models are designed to be more efficient, with reduced latency and improved performance, making them suitable for a wide range of applications.

128K context length allows Llama to capture even more nuanced relationships in data.

Llama models are trained on over 15 trillion tokens from online public data sources to better comprehend language intricacies.

Llama 3.2 is multilingual and supports eight languages including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.

The Amazon Bedrock managed API makes using Llama models easier than ever. Organizations of all sizes can access the power of Llama without worrying about the underlying infrastructure. Since Amazon Bedrock is serverless, you don't have to manage any infrastructure, and you can securely integrate and deploy the generative AI capabilities of Llama into your applications using the AWS services you are already familiar with. This means you can focus on what you do best—building your AI applications.

Meet Llama

For over the past decade, Meta has been focused on putting tools into the hands of developers, and fostering collaboration and advancements among developers, researchers, and organizations. Llama models are available in a range of parameter sizes, enabling developers to select the model that best fits their needs and inference budget. Llama models in Amazon Bedrock open up a world of possibilities because developers don't need to worry about scalability or managing infrastructure. Amazon Bedrock is a very simple turnkey way for developers to get started using Llama.

Use cases

Llama models excel at image understanding and visual reasoning, language nuances, contextual understanding, and complex tasks, such as visual data analysis, image captioning, dialogue generation, and translation, and can handle multistep tasks seamlessly. Additional use cases Llama models are a great fit for include sophisticated visual reasoning and understanding, image-text-retrieval, visual grounding, document visual question answering, text summarization and accuracy, text classification, sentiment analysis and nuance reasoning, language modeling, dialog systems, code generation, and following instructions.

Model versions

Llama 3.3 70B

Text-only 70B instruction-tuned model that provides enhanced performance relative to Llama 3.1 70B–and to Llama 3.2 90B when used for text-only applications. Llama 3.3 70B delivers similar performance to Llama 3.1 405B while requiring only a fraction of the computational resources.

Max tokens: 128K

Languages: English, German, French, Italian, Portuguese, Spanish, and Thai

Fine-tuning supported: No

Supported use cases: Conversational AI designed for content creation, enterprise applications, and research, offering advanced language understanding capabilities, including text summarization, classification, sentiment analysis, and code generation. The model also supports the ability to leverage model outputs to improve other models including synthetic data generation and distillation

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Llama 3.2 90B

Multimodal model that takes both text and image inputs and outputs. Ideal for applications requiring sophisticated visual intelligence, such as image analysis, document processing, multimodal chatbots, and autonomous systems.

Max tokens: 128K

Languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai

Fine-tuning supported: Yes

Supported use cases: Image understanding, visual reasoning, and multimodal interaction, enabling advanced applications such as image captioning, image-text retrieval, visual grounding, visual question answering, and document visual question answering, with a unique ability to reason and draw conclusions from visual and textual inputs

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Llama 3.2 11B

Multimodal model that takes both text and image inputs and outputs. Ideal for applications requiring sophisticated visual intelligence, such as image analysis, document processing, and multimodal chatbots.

Max tokens: 128K

Languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.

Fine-tuning supported: Yes

Supported use cases: Image understanding, visual reasoning, and multimodal interaction, enabling advanced applications such as image captioning, image-text retrieval, visual grounding, visual question answering, and document visual question answering

Read the blog

Llama 3.2 3B

Text-only lightweight model built to deliver highly accurate and relevant results. Designed for applications requiring low-latency inferencing and limited computational resources. Ideal for query and prompt rewriting, mobile AI-powered writing assistants, and customer service applications, particularly on edge devices where its efficiency and low latency enable seamless integration into various applications, including mobile AI-powered writing assistants and customer service chatbots.

Max tokens: 128K

Languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai

Fine-tuning supported: Yes

Supported use cases: Advanced text generation, summarization, sentiment analysis, emotional intelligence, contextual understanding, and common sense reasoning

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Nomura uses Llama models from Meta in Amazon Bedrock to democratize generative AI

Aniruddh Singh, Nomura's Executive Director and Enterprise Architect, outlines the financial institution’s journey to democratize generative AI firm-wide using Amazon Bedrock and Llama models from Meta. Amazon Bedrock provides critical access to leading foundation models like Llama, enabling seamless integration. Llama offers key benefits to Nomura, including faster innovation, transparency, bias guardrails, and robust performance across text summarization, code generation, log analysis, and document processing. 

TaskUs revolutionizes customer experiences using Llama models from Meta in Amazon Bedrock

TaskUs, a leading provider of outsourced digital services and next-generation customer experience to the world’s most innovative companies, helps its clients represent, protect, and grow their brands. Its innovative TaskGPT platform, powered by Amazon Bedrock and Llama models from Meta, empowers teammates to deliver exceptional service. TaskUs builds tools on TaskGPT that leverage Amazon Bedrock and Llama for cost-effective paraphrasing, content generation, comprehension, and complex task handling.