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  1. Using The Platform
  2. Supported Models

Which LLM Should You Choose?

A guide for choosing the best LLM API for your use case

PreviousSupported ModelsNextComparative Analysis of Large Language Models in Vision Tasks

Last updated 11 months ago

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eneral Recommendation

Use Case
Use Case Description
Preferred Model(s)

General Tasks (Open-Ended)

Handle diverse requests without specific instructions. Relies on the model's broad knowledge and understanding.

GPT-4-Turbo

General Tasks (Guided)

Handling a wide range of tasks with the help of few-shot or chain-of-thought prompting, enabling smaller, faster models to produce reasonably good quality outputs with reduced latency and cost.

Claude 3 Haiku

Low Latency & Cost-Sensitive

Prioritize quick responses and affordability over the absolute best output quality. Ideal for real-time or high-volume applications.

Claude 3 Haiku/Mixtral

Auto Prompt Rewriter and Refinement

Automatically refine prompts for better results. Understands intent and suggests changes for improved effectiveness with smaller LLMs.

GPT-4-Turbo/ Claude 3 Opus

Core Applications:

Use Case
Model

Language Understanding and Generation:

  • Content Creation and Summarization

  • Language Translation and Localization

  • Conversational AI and Virtual Assistants (Chatbot)

  • Sentiment Analysis

  • Intelligent Writing Assistance

Claude 3 Haiku

Claude 3 Opus for Multilingual

Computer Vision and Multimodal Integration:

  • Image Captioning

  • Visual Question Answering

  • Multimodal Data Processing for Enhanced Insights

Claude 3 Haiku

Information Management:

  • Data Retrieval and Analysis

  • Knowledge Management and Research Support

  • Personalization and Recommendation Systems

  • Visual/Text Search

Option: Retrieval-augmented generation (RAG) Model: Claude 3 Haiku/ Command R+

Specialized Applications:

Use Case
Model

Code and Automation:

  • Development and Coding Support: Automating code generation and offering software development assistance.

  • Operational Efficiency: Enhancing process automation and intelligent document processing for improved workflow.

  • Content and Security Management: Implementing content moderation, filtering, and mechanisms for fraud detection and prevention.

Claude 3 Opus

Business and Commerce:

  • E-commerce and Retail Enhancements: Optimizing online shopping experiences and supporting retail operations.

  • Customer Engagement: Utilizing chatbots for service and support, and deploying personalized email marketing campaigns.

  • Marketing and Sales: Developing targeted marketing strategies, generating product descriptions, and leveraging intelligent upselling and cross-selling.

  • Market Insights: Conducting market research, analyzing customer reviews, and forecasting demand.

  • Product Management: Automating product categorization, tagging, and inventory management.

Claude 3 Haiku

Education and Learning:

  • Personalized Education: Creating adaptive learning materials and tools tailored to individual learning styles and needs.

Claude 3 Opus

Geospatial and Environmental Analysis:

  • Spatial Data Insights: Offering mapping and spatial data analysis for various applications.

Claude-3 Sonnet

Performance vs Price Analysis

Input token price: This graph illustrates a comparison of popular large language models (LLMs), plotting 'LMSYS Better Arena Elo' against 'Price per 1M Token (Input)', both on a logarithmic scale.