Clarity Platform Agents

The Clarity platform offers multiple agents, enabling you to experiment with agents that use different AI models and choose the appropriate one for your use case. This page provides a comprehensive comparison of the agents available on the Clarity platform to help you understand their capabilities, differences, and how to choose the right one for your needs.

GPT-4o agent

The default agent in Clarity uses OpenAI’s Chat GPT-4o model, an advanced large language model developed to handle complex, multi-step tasks with a high degree of accuracy. GPT-4o excels at generating nuanced and contextually relevant responses, making this agent suitable for sophisticated applications and datasets.

GPT-4o-mini agent

This agent uses Open AI’s GPT-4o mini model, a more compact and cost-effective version of GPT-4o. It offers a balance between performance and resource efficiency, making it a significantly more environmentally friendly choice while maintaining robust performance. GPT-4o mini is optimal for basic and lightweight tasks and surpasses other small models on academic benchmarks, while supporting the same range of languages as GPT-4o. For a more detailed breakdown of the model evaluation benchmark and additional information on GPT-4o mini, please refer to OpenAI’s documentation.

Claude-3-5-Sonnet agent

This agent uses Anthropic’s Claude 3.5 Sonnet model to generate text responses and generate code and can generate images using DALL·E  3.  The Claude 3.5 Sonnet model is suitable for coding tasks, summarizing and reasoning on large amounts of text, and supporting creative and academic writing. The Claude-3-5-Sonnet agent will support file uploads in future releases.

Differences between the agents in Clarity

Feature GPT-4o GPT-4o-mini Claude-3-5-Sonnet
Performance[i] Higher accuracy, coherence, and fluency Lower accuracy, coherence, and fluency Higher accuracy, coherence, and fluency
Environmental Impact Higher energy consumption due to greater computational requirements Lower energy consumption, making it more eco-friendly Higher energy consumption due to greater computational requirements
Use Cases Suitable for complex queries, creative writing, and detailed analysis Geared towards basic tasks, and lower-resource applications Suitable for complex queries, creative writing and code generation
Image Generation Yes, using DALL·E 3 Yes, using DALL·E 3 Yes, using DALL·E
Code execution Can execute code to create charts or calculate answers Can execute code to create charts or calculate answers No (cannot execute code to provide analysis but can output code when prompted)
File uploads  Yes Yes No
Knowledge cut-off October 2023 October 2023 April 2024

How responses differ by agent

Below are some example prompts along with responses from GPT-4o, GPT-4o-mini, and Claude-3-5-Sonnet.  The first example shows that for simple tasks, such as summarization, there is little difference between GPT-4o and GPT-4o-mini. This similarity supports the use of the more environmentally friendly GPT-4o-mini agent. 

The second example illustrates that for more complex tasks requiring analysis, there is a noticeable difference in the responses generated by the agents. In this instance, GPT-4o concentrates on offering task-specific recommendations, while GPT-4o-mini additionally identifies the challenges involved despite not including that in the prompt request.

Summarizing Text Example

Analysis Example

[i]LLM Stats provides scores for these models used by these agents on common AI benchmarks.