We support a number of different models provided by multiple AI service providers, namely OpenAI, Anthropic, Minstral, Llama, Cohere, Gemini and many more, each with their own series of models. Each model has its own unique specifications and use cases, and in this guide we will explain how to choose the best model for your use case.
Choosing between AI Models
OpenAI Models
1. GPT-4
| Attribute |
Details |
| Description |
The original GPT-4 model is a large multimodal model that accepts both text and image inputs, providing advanced reasoning and problem-solving capabilities. |
| Costs |
20 messages per user query and chat response |
| Strengths |
Exceptional at complex language tasks, capable of generating coherent and contextually relevant text. It offers high accuracy and is optimized for chat applications. |
| Use Cases |
Suitable for applications requiring deep understanding and generation of text, such as customer support, content creation, and educational tools. |
2. GPT-4 Turbo
| Attribute |
Details |
| Description |
A variant of GPT-4 that is optimized for speed and efficiency while maintaining high performance. |
| Costs |
10 messages per user query and chat response |
| Image Reading Capabilities |
Available |
| Strengths |
Faster response times compared to the standard GPT-4, making it ideal for real-time applications. Supports vision capabilities and function calling. |
| Weaknesses |
More expensive than the GPT-4o models due to higher intelligence and resources required |
| Use Cases |
Best for chatbots and applications needing quick interactions, such as virtual assistants and interactive games. |
3. GPT-4o
| Attribute |
Details |
| Description |
The "omni" model that is multimodal, accepting both text and image inputs, designed for a broader range of tasks. |
| Costs |
5 messages per user query and chat response |
| Image Reading Capabilities |
Available |
| Strengths |
Higher intelligence than previous models, cost-effective, and capable of handling complex tasks efficiently. |
| Weaknesses |
Complexity in use, higher risk of toxic output, potential inconsistencies in response quality |
| Use Cases |
Ideal for applications that require both text and image processing, such as content creation, data analysis, and customer service. |
4. GPT-4o Mini
| Attribute |
Details |
| Description |
A smaller and more affordable version of GPT-4o, optimized for lightweight tasks while still offering advanced capabilities. |
| Costs |
1 messages per user query and chat response |
| Strengths |
Cost-effective, fast, and capable of handling various tasks. |
| Weaknesses |
Reduced performance on complex tasks, limited functionality compared to larger models, susceptibility to errors |
| Use Cases |
Suitable for smaller applications, such as chatbots, virtual assistants, and basic content generation where speed and cost are priorities. |
*GPT-4o mini 60k context is an alternative model to the GPT-4mini model provided that provides for better quality answers due to a larger context window included
In Summary: