Since OpenAI launched, it has introduced a variety of models, each designed for specific tasks. With so many options, choosing the right one for your needs can be challenging. OpenAI is divided into two kinds of models: reasoning models and GPT models. While both are powerful, they serve different purposes. But what sets them apart? Let’s find out.
Understanding OpenAI’s Models
OpenAI provides two main categories of models:
- Reasoning Models: These models use chain-of-thought reasoning to break down complex tasks into logical steps, making them highly effective for problem-solving in STEM, research, and strategic decision-making.
- GPT Models: These are fast, versatile, cost-effective, and customizable, making them ideal for general AI applications like text generation, customer interactions, and content creation.
| Model | Performance and capabilities | Cost and efficiency | Processing speed | Use Cases |
| o1 | Optimized for deep reasoning and multi-domain problem-solving | High operational costs due to intensive processing | Longer response times | Advanced research, complex problem-solving |
| o1 – mini | Balances reasoning depth with speed and cost-efficiency; strong in STEM | Lower cost | Faster responses | Specialized, time-sensitive STEM tasks (coding, cybersecurity) |
| o3 | Enhanced reasoning for complex STEM tasks using “chain of thought” | Higher computational cost | Longer processing times | Advanced math, coding, and problem-solving |
| o3 – mini | Strong performance in STEM fields; function calling & structured outputs | Cost-efficient | Faster responses, lower latency | Efficient reasoning in science, math, and coding |
| o4 | Advanced AI reasoning across multiple domains | Higher operational costs | Balanced reasoning and speed | Research, complex problem-solving |
| o4 – mini | Efficient variant of o4 with lower costs | More affordable | Faster processing while maintaining reasoning depth | Broad range of applications needing efficiency & capability |
Decision Guide: Which model should you choose?
Wondering which model you should use for your needs? We have made it simple for you with our decision guide to select which model you should use:
ChatGPT decision guide:
Need deep reasoning for complex problems?
→ Choose o1 or o4.
Need cost-effective but strong reasoning?
→ Choose o1-mini or o3-mini.
Need fast, structured outputs for coding and STEM?
→ Choose o3 or o3-mini.
Need a balance between power and efficiency?
→ Choose o4-mini.
Need general AI for content, customer support, or quick responses?
→ Choose GPT-4o or GPT-4-mini.
Common misconceptions about ChatGPT models
- “More expensive models are always better”
Not necessarily! Some tasks require efficiency over deep reasoning. - “GPT-4o is just a chatbot”
It’s actually a highly capable AI that can handle summarization, brainstorming, and even technical support. - “Mini versions are less useful.”
In many cases, mini variants provide the best balance of cost and speed for real-world applications.
How DataNorth Can Help
At DataNorth, we offer ChatGPT workshops to help you understand and implement AI effectively within your organization. Beyond workshops, we specialize in integrating and customizing ChatGPT for your specific workflows. Whether you require fine-tuning, tailored AI solutions, or integration into existing workflows, our expertise ensures that ChatGPT delivers maximum efficiency and relevance to your business.
For more information, you can get in contact with us and discuss how to implement AI in your organization.
