This guide provides an in-depth look at the diverse foundation models (FMs) available through Amazon Bedrock. It examines the unique capabilities and ideal use cases of each model and offers a detailed breakdown of their pricing, helping you identify the best FM for your generative AI needs.
Exploring Foundation Models in AWS Bedrock
Amazon Bedrock offers a wide selection of foundation models, each tailored for different applications. The available models include AI21 Labs’ Jurassic, Anthropic’s Claude, Cohere’s Command and Embed, Meta’s Llama 2, Stability AI’s Stable Diffusion, and Amazon’s Titan models. Depending on the requirements of your project, you can select the model that best aligns with your objectives.
Foundation Models on Amazon Bedrock: Versions and Pricing
Below is a detailed list of all the foundation models offered on Amazon Bedrock, along with their respective capabilities, versions, and pricing.
| Foundation Model | Model Version | Max Capacity | Distinct Features & Languages | Supported Use Cases & Applications | Pricing |
|---|---|---|---|---|---|
| AI21 Labs Jurassic | Jurassic-2 Ultra | 8,192 tokens | Advanced text generation (English, Spanish, French, German, Portuguese, Italian, Dutch) | Intricate QA, summarization, finance, legal, research sectors | $0.0188 per 1,000 tokens |
| Jurassic-2 Mid | 8,192 tokens | Text generation in multiple languages | QA, content creation, info extraction across industries | $0.0125 per 1,000 tokens | |
| Anthropic Claude | Claude 2.1 | 200K tokens | High-capacity text generation, multiple languages | Analysis, trend forecasting, document comparison | $0.00800 input, $0.02400 output per 1,000 tokens |
| Claude 2.0 | 100K tokens | Creative content generation, coding support, multiple languages | Creative dialogue, tech development, educational content | $0.00800 input, $0.02400 output per 1,000 tokens | |
| Claude 1.3 | 100K tokens | Writing assistance, advisory capabilities, multiple languages | Document editing, coding, advisory across sectors | $0.00800 input, $0.02400 output per 1,000 tokens | |
| Claude Instant | 100K tokens | Rapid response generation, multiple languages | Fast dialogue, summary, text analysis, customer support | $0.00163 input, $0.00551 output per 1,000 tokens | |
| Cohere Command & Embed | Command | 4K tokens | Advanced chat and text generation, English | Customer support, content creation for marketing | $0.0015 input, $0.0020 output per 1,000 tokens |
| Command Light | 4K tokens | Efficient text generation, English | Small-scale chat, content tasks, business communications | $0.0003 input, $0.0006 output per 1,000 tokens | |
| Embed – English | 1024 dimensions | Semantic search, English | Precise text retrieval, classification in knowledge management | $0.0001 per 1,000 tokens | |
| Embed – Multilingual | 1024 dimensions | Global reach with support for 100+ languages | Multilingual semantic search, data clustering for business | $0.0001 per 1,000 tokens | |
| Meta Llama 2 | Llama-2-13b-chat | 4K tokens | Optimized for dialogue, English | Language translation, text classification, multilingual communication | $0.00075 input, $0.00100 output per 1,000 tokens |
| Llama-2-70b-chat | 4K tokens | Large-scale language modeling, English | Detailed text generation, customer service, creative industries | $0.00195 input, $0.00256 output per 1,000 tokens | |
| Stable Diffusion | SDXL 1.0 | 77-token limit for prompts | Native 1024×1024 image generation, English | High-quality image creation for advertising, gaming, media | Standard: $0.04, Premium: $0.08 per image (1024×1024) |
| SDXL 0.8 | 77-token limit for prompts | Text-to-image model, English | Creative asset development in marketing, media, artistic styles | Standard: $0.018, Premium: $0.036 per image (512×512) | |
| Amazon Titan | Titan Text Express | 8K tokens | High-performance text model, 100+ languages | Content creation, classification, open-ended Q&A | $0.0008 input, $0.0016 output per 1,000 tokens |
| Titan Text Lite | 4K tokens | Cost-effective text generation, English | Summarization, copywriting in marketing and communications | $0.0003 input, $0.0004 output per 1,000 tokens | |
| Titan Text Embeddings | 8K tokens | Text translation to numerical representations, 25+ languages | Semantic similarity, data clustering for analysis | $0.0001 per 1,000 tokens | |
| Titan Multimodal Embeddings | 128 tokens, 25 MB images | Multimodal (text and image) search, English | Contextually relevant search, recommendation in e-commerce | $0.0008 per 1,000 tokens; $0.00006 per image | |
| Titan Image Generator | 77 tokens, 25 MB images | High-quality image generation using text prompts, English | Image creation and editing for advertising, e-commerce | 512×512: $0.008, 1024×1024: $0.01 per image |
Which Foundation Model to use on AWS Bedrock?
When to Choose Claude on AWS Bedrock
There are several instances where using Claude as your Foundation Model on AWS is ideal. Here are the most popular use cases:
- You require a model that emphasizes safety and reliability in generative AI solutions.
- Tasks involve multi-faceted dialogue, creative content generation, or complex problem-solving.
- Speed and cost-effectiveness are key considerations, as seen in Claude Instant.
Claude’s ethical AI framework and adaptable nature make it a top contender for a wide range of use cases where safety, accuracy, and creativity are paramount, making it an excellent choice for businesses that prioritize reliability and versatility in their AI-powered applications.
When to Use Cohere Models on AWS Bedrock?
Choose Cohere’s Command & Embed models for content that is confidential, contains identifiable information, or sensitive business data:
- Advanced chatbot functionalities and content generation.
- Multilingual text processing and semantic searches.
- Privacy-centric applications with a need for model customization.
- Efficient summarization, classification, and clustering tasks in diverse business scenarios.
Cohere’s Command & Embed models on AWS Bedrock offer a robust solution for businesses requiring privacy, customization, and versatility, making them an excellent choice for AI-powered applications where security and flexibility are essential.
When to Use Jurassic on AWS Bedrock?
Whether for intricate reasoning, content generation, or natural language processing, Jurassic provides the necessary tools for innovative, AI-driven solutions. Jurassic’s models on AWS Bedrock are ideal when:
- You need high-quality, nuanced text generation for intricate tasks.
- Your application demands quick, natural language processing for real-time responses.
- You’re seeking a balance between exceptional quality and cost-efficiency.
- Your tasks require deep reasoning, logic, and language comprehension.
Jurassic on AWS Bedrock excels in delivering sophisticated, high-quality text generation and natural language understanding, making it an ideal solution for complex reasoning, content creation, and real-time applications.
When to Use Llama 2 on AWS Bedrock?
Llama 2’s models are a prime choice in scenarios where:
- Dialogue and interaction-focused AI applications are a priority.
- Tasks require a balance between comprehensive language understanding and concise model deployment.
- There’s a need for a wide-ranging scale of tasks, from basic text classification to elaborate language modeling and text generation.
Meta Llama 2’s models on AWS Bedrock provide adaptable, safety-focused solutions for a variety of dialogue-based applications, offering high performance for both large and small-scale AI tasks.
When to Use Stable Diffusion XL on AWS Bedrock?
Stable Diffusion XL is the ideal choice for applications that demand:
- High-fidelity, photorealistic image generation from textual descriptions.
- Creative brainstorming and asset creation for advertising, media, and entertainment domains.
- Innovative character and world-building in gaming and metaverse environments.
Stable Diffusion XL on AWS Bedrock empowers businesses and creators with high-quality, text-to-image generation, making it the go-to choice for industries that require intricate and realistic visuals for a wide range of creative and marketing applications.
When to Use Amazon Titan on AWS Bedrock?
Opt for Amazon Titan’s models when your application requires:
- Diverse and high-performing AI solutions for text, image, and multimodal tasks.
- A responsible AI approach with built-in mechanisms for content safety.
- Customization options to tailor models to specific organizational needs and domains.
- Generating high-quality, realistic images or enhancing search and recommendation systems.
Amazon Titan on AWS Bedrock provides a comprehensive suite of AI models that offer flexibility, safety, and performance across a wide range of applications, making it a reliable choice for businesses seeking robust and responsible AI solutions.
Conclusion
Choosing the right AWS Bedrock model depends on the specific needs of your project, including factors like the type of application, privacy requirements, desired performance, and cost considerations. With options ranging from Claude’s safety-focused capabilities to Cohere’s customizable privacy features, Jurassic’s deep reasoning, and Stable Diffusion XL’s creative potential, each model brings unique strengths to the table. By understanding the features, use cases, and customization options of each model, you can select the best solution for your business, ensuring a balance of accuracy, creativity, and efficiency tailored to your AI goals.
