Comparison of AI Models o3-mini, o1, 4o, DeepSeek R1: Costs, Performance, and Applications

AI models are now essential tools for automation and process optimization. Each of them: o3-mini, o3 mini-high, ChatGPT o1, or DeepSeek R1—has specific applications and operational differences.

This article provides a comparison of their performance, response quality, and usage costs to help you choose the most suitable model for your needs.

Differences Between o3-mini, o3 mini-high, ChatGPT o1, and DeepSeek R1

o3-mini, o3 mini-high, ChatGPT o1, and DeepSeek R1 are models optimized for different applications, from automation to data analysis and coding. Each offers different performance parameters and usage costs.

1. Architecture and Performance

• o3-mini: A compact AI model optimized for fast processing and low resource consumption. Suitable for general applications and everyday automation.
• o3 mini-high: A more powerful version of o3-mini, delivering better results in precision-demanding tasks such as programming and technical analysis.
• ChatGPT o1: A model optimized for longer interactions and more complex problems, with a focus on logical accuracy.
• DeepSeek R1: A high-performance model competing with OpenAI, designed for working with large datasets while maintaining high efficiency.

2. Usage Costs

• o3-mini: A cost-effective solution designed for minimal token processing costs.
• o3 mini-high: Slightly more expensive than the mini version but offering higher-quality results, especially for more demanding applications.
• ChatGPT o1: A cost-optimized model designed for large-scale operations where balancing price and performance is crucial.
• DeepSeek R1: Competitively priced, often chosen in environments requiring high computing power with a limited budget.

3. Practical Applications

• o3-mini: Suitable for basic automation, chatbots, and less demanding natural language processing tasks.
• o3 mini-high: A better option for developers and data analysts where precision and performance matter.
• ChatGPT o1: Ideal for companies requiring detailed analyses, reporting, or support in complex user interactions.
• DeepSeek R1: A model selected for working with large datasets, information exploration, and more advanced text analysis.

4. Response Quality

• o3-mini: Fast and efficient responses, though less precise than the high version.
• o3 mini-high: Higher response quality in coding, mathematics, and analysis.
• ChatGPT o1: Focused on accuracy and long-term consistency in responses.
• DeepSeek R1: Solid quality in analyzing large datasets, though not always matching OpenAI’s precision.

Each model has its specific applications: o3-mini for daily operations, o3 mini-high for more demanding technical tasks, ChatGPT o1 for complex analyses, and DeepSeek R1 for handling large datasets. The choice depends on user priorities—speed, precision, or cost.

Performance and Response Quality: o3-mini and o3 mini-high

The o3-mini model delivers significant results in coding, mathematics, and general knowledge tasks, outperforming the o1 model even at a medium reasoning effort level. At the highest reasoning effort level, it achieves a 0.846 performance score in LiveBench Coding Average, an improvement over o1 (0.674).

Best Applications and Test Results

1. Coding (LiveBench)

- o3 mini-high scores 0.833 in "Code Completion", clearly surpassing o1 (0.72), making it the better choice for programming-related tasks.

2. General Knowledge and Mathematics

- In mathematical tests, o3 mini-high achieves 97.9% ,and in general knowledge evaluation, it scores 86.9%, outperforming other models in this category.

3. Security and Response Consistency

- Thanks to "deliberative alignment" techniques, the o3-mini model outperforms GPT-4o and o1 in security tests, providing precise and consistent responses while effectively avoiding jailbreaks.

4. Processing Speed

- A/B tests showed that the average response time for o3-mini is 7.7 seconds, which is 24% faster than o1-mini (10.16 seconds), ensuring better performance in applications requiring fast processing.

Advanced Features for Developers

The o3-mini model supports features such as function calling, structured outputs, and developer messages, making it production-ready. Streaming support enables smooth real-time processing of large datasets, which is crucial for applications requiring fast responses.

Flexibility and Limitations

The model offers three levels of "reasoning effort" (low, medium, high) to adapt to different needs. The high version provides the highest precision; however, o3-mini does not support visual reasoning tasks, where ChatGPT o1 performs better.

Summary of Model Differences

The o3-mini and its more advanced version, o3 mini-high, are leading AI models in STEM fields. They offer exceptional response quality, flexibility, and cost efficiency, outperforming previous models in most performance and security tests. With advanced feature support and high-speed processing, they are the best choice for tasks requiring complex reasoning and analysis.

If you want to learn more about the performance and response quality of 4o and o1, read our article.

Automation with o3-mini and o3 mini-high

The o3-mini and o3 mini-high models are highly effective in automating processes across various business and technical environments. Thanks to their processing flexibility, advanced features, and high performance, they excel in tasks requiring both precision and speed.

1. Automating Simple Processes with o3-mini

The o3-mini model is optimized for fast processing of simple tasks, such as:

• Real-time report generation
• Automatic classification of text data
• Chatbot and customer support system management

With function calling and structured outputs support, the model easily integrates with existing systems, streamlining the automation of repetitive processes.

2. Advanced Automation with o3 mini-high

The o3 mini-high model is the ideal solution for more complex automation processes, such as:

• Code generation and programming analysis
• Advanced financial and predictive data analysis
• Automatic error detection and reporting in large datasets

With its high reasoning effort, this model delivers greater accuracy and reliability in tasks requiring advanced thinking.

3. Developer Support

Both models features useful for automating technical tasks, including:

• Streaming: Enables smooth real-time data processing, reducing processing times for systems requiring dynamic interaction.
• Developer messages: Help create more intuitive interfaces and processes for end users.

4. Application Examples

• o3-mini: Automating customer support in e-commerce – quickly generating responses to customer inquiries.
• o3 mini-high: Implementing a sales performance analysis system – automatically generating reports and detecting anomalies in data.

Cost per Token and Savings with Batch API

Token processing cost is a key factor when choosing an AI model. Below are the current rates for selected models, as well as discounted costs available through Batch API, which reduces expenses by 50% while delivering results within 24 hours.

For detailed pricing, check the OpenAI website.

1. Standard Token Costs

GPT-4o

• Input cost: $2.50 / 1M tokens
• Output cost: $10.00 / 1M tokens

GPT-4o mini

• Input cost: $0.15 / 1M tokens
• Output cost: $0.60 / 1M tokens

o1

• Input cost: $15.00 / 1M tokens
• Output cost: $60.00 / 1M tokens

o3-mini

• Input cost: $1.10 / 1M tokens
• Output cost: $4.40 / 1M tokens

DeepSeek R1

• Input cost: Free
• Output cost: Free

2. Token Costs with Batch API (50% Discount)

Using Batch API can reduce costs by 50%, delivering results within 24 hours. Below are the discounted rates for selected models:

GPT-4o

• Input cost: $1.25 / 1M tokens
• Output cost: $5.00 / 1M tokens

GPT-4o mini

• Input cost: $0.075 / 1M tokens
• Output cost: $0.30 / 1M tokens

o1

• Input cost: $7.50 / 1M tokens
• Output cost: $30.00 / 1M tokens

o3-mini

• Input cost: $0.55 / 1M tokens
• Output cost: $2.20 / 1M tokens

DeepSeek R1

Does not use Batch API

3. How Does Batch API Work and When Should You Use It?

Batch API enables bulk processing of large data volumes, offering significant cost savings. It is the ideal solution for:

• Companies processing millions of tokens daily, where maximum cost reduction is essential.
• Tasks that do not require immediate responses - models return results within 24 hours.
• Automated report generation, text analysis, code processing, and historical data analysis.

Summary of Model Costs

Batch API cuts costs in half, making it the most affordable processing method for businesses and developers using AI at scale. o3-mini and o3 mini-high are the most cost-effective models for automation, coding, and STEM-related tasks.

GPT-4o provides the highest response quality, while DeepSeek R1 remains a free alternative for public users.

With Batch API, you can significantly reduce costs without compromising performance, as long as 24-hour response times are acceptable.

How to Choose the Right Model?

🔹 GPT-4o – If you need a model for user interactions, such as chatbots, customer support, or content generation, GPT-4o is the best option. It offers the highest quality and better context understanding.

🔹 o1 – If your priority is analysis and summaries, such as financial reports, business insights, or large-scale content generation, choose o1. It handles logical processing well.

🔹 o3-mini / mini-high – If fast and efficient code processing, mathematical analysis, or automation of repetitive business tasks is crucial, o3-mini is the best choice. Mini-high is ideal for higher-precision tasks, such as bug detection in code.

🔹 DeepSeek R1 – If zero cost is the main factor and your tasks involve mass text processing, such as document analysis, scientific research, or AI testing, DeepSeek R1 is the right choice.

Summary

Each model - GPT-4o, o1, o3-mini, o3 mini-high, and DeepSeek R1 has different use cases and cost structures.

• GPT-4o provides the highest quality and excels in user interactions.
• o1 is great for logic-based analysis and reporting.
• o3-mini and mini-high specialize in coding, mathematics, and automation.
• DeepSeek R1 is a free option for large-scale data analysis.

With Batch API, you can cut costs by 50%, making it the best choice for companies processing large volumes of data. o3-mini and mini-high are the most cost-effective for STEM applications, while GPT-4o remains the best for high-quality responses.

The best model depends on your priorities:

• If quality and context understanding matter most, choose GPT-4o.
• For analysis and reporting, o1 is a strong option.
• If automation and coding are key, go for o3-mini or o3 mini-high.
• For large-scale, cost-free tasks, DeepSeek R1 is the best fit.