OpenAI’s o1 Mini vs o1 Preview: A Comprehensive Comparison

OpenAI’s recent release of the o1 series has sparked significant interest in the AI community. The two models, o1 Mini and o1 Preview, offer unique capabilities and trade-offs. This article provides an in-depth comparison of these models, focusing on their performance, pricing, and use cases.

Overview of OpenAI’s o1 Mini and o1 Preview

Both o1 Mini and o1 Preview were released on September 12, 2024, marking a new era in OpenAI’s model lineup. These models share several characteristics:

• Input Context Window: Both models support a 128K token input context window.
• Knowledge Cutoff: The knowledge base for both models is limited to October 2023.
• Provider: OpenAI is the provider for both models.

However, there are notable differences:

• Maximum Output Tokens: o1 Mini can generate up to 65.5K tokens in a single request, while o1 Preview is limited to 32.8K tokens.
• Pricing: o1 Mini is significantly cheaper, with input costs at $3.00 per million tokens and output costs at $12.00 per million tokens. In contrast, o1 Preview charges $15.00 per million tokens for input and $60.00 per million tokens for output.

Performance Benchmarks: o1-preview vs o1-mini vs GPT-4o

While comprehensive benchmarks are still being compiled, initial tests and OpenAI’s disclosures provide insights into the models’ performance across various tasks.

Mathematics

In the American Invitational Mathematics Examination (AIME), a high school math competition:

• o1 Mini: 70.0%
• o1 Preview: 44.6%

This performance puts o1 Mini on par with approximately the top 500 US high school students in mathematics.

Coding

On the Codeforces competition website:

• o1 Mini: 1650 Elo
• o1 Preview: 1258 Elo

The o1 Mini’s Elo score places it at approximately the 86th percentile of programmers competing on the Codeforces platform.

STEM Reasoning

On certain academic benchmarks requiring reasoning:

• GPQA (science): o1 Mini outperforms GPT-4o
• MATH-500: o1 Mini outperforms GPT-4o

However, it’s important to note that o1 Mini lags behind o1 Preview on GPQA due to its more limited broad world knowledge.

Human Preference Evaluation

In comparisons with GPT-4o on challenging, open-ended prompts:

• o1 Mini is preferred in reasoning-heavy domains
• o1 Mini is not preferred in language-focused domains

Speed and Efficiency

One of the most significant advantages of o1 Mini is its speed. In a comparison of response times for a word reasoning question:

• o1 Mini: 3–5x faster than GPT-4o
• o1 Preview: Faster than GPT-4o, but slower than o1 Mini

This speed advantage makes o1 Mini particularly attractive for applications requiring quick responses or processing large volumes of data.

Specialized Capabilities

o1 Mini: STEM Focus

o1 Mini is specifically optimized for STEM reasoning during pretraining. This specialization allows it to perform exceptionally well in areas such as:

• Mathematics
• Coding
• Scientific reasoning

However, this focus comes at the cost of broader knowledge. o1 Mini’s performance on non-STEM topics such as dates, biographies, and general trivia is comparable to smaller language models like GPT-4o mini.

o1 Preview: Broader Capabilities

While o1 Preview doesn’t match o1 Mini’s performance in STEM areas, it offers a more balanced set of capabilities. It performs better on tasks requiring:

• General knowledge
• Language understanding
• Broad reasoning across various domains

Safety and Robustness

Both models have been trained using OpenAI’s alignment and safety techniques. However, o1 Mini shows some advantages:

• 59% higher jailbreak robustness on an internal version of the StrongREJECT dataset compared to GPT-4o
• Underwent the same rigorous safety evaluations and external red-teaming as o1 Preview

This enhanced safety profile makes o1 Mini a compelling choice for applications where security and adherence to guidelines are critical.

Use Cases and Applications

o1 Mini

1. STEM Education: Ideal for creating problem sets, explaining complex concepts, and assisting with homework in mathematics, physics, and other STEM fields.
2. Coding Assistance: Excellent for code generation, debugging, and explaining programming concepts across various languages.
3. Scientific Research: Can assist in data analysis, hypothesis generation, and literature review in STEM fields.
4. Rapid Prototyping: Its speed makes it suitable for quick iterations in software development and engineering design.
5. Automated Reasoning: Useful in applications requiring fast, logical decision-making based on structured data.

o1 Preview

1. Content Creation: Better suited for generating diverse content across various topics due to its broader knowledge base.
2. Language Translation: More adept at nuanced translations and understanding context in multiple languages.
3. Customer Service: Can handle a wider range of customer inquiries across different industries.
4. Market Analysis: Better equipped to process and analyze diverse market trends and consumer behaviors.
5. General Research: More effective for interdisciplinary research that spans beyond STEM fields.

Cost Considerations

The pricing structure of these models plays a crucial role in their adoption:

• o1 Mini is approximately 80% cheaper than o1 Preview
• This cost efficiency makes o1 Mini attractive for large-scale applications, especially in STEM fields

For organizations primarily focused on STEM applications, o1 Mini offers a significant cost advantage without compromising on performance in these areas.

Limitations and Future Developments

o1 Mini

• Limited knowledge in non-STEM areas
• May struggle with tasks requiring broad cultural or historical context

OpenAI has indicated plans to address these limitations in future versions, potentially expanding o1 Mini’s capabilities to other modalities and specialties outside of STEM.

o1 Preview

• Higher cost may limit its use in some applications
• Slower processing speed compared to o1 Mini

Future updates may focus on improving processing speed and efficiency to make o1 Preview more competitive in areas where o1 Mini currently excels.

Integration and Accessibility

Both models are available through OpenAI’s API, with some differences in access:

• Available in ChatGPT Plus (including Team and Enterprise users)
• API access for developers on tier 5 of API usage
• In ChatGPT, o1 Preview has a limit of 30 messages per week
• o1 Mini has a higher limit of 50 messages per week

After reaching these limits, users are required to switch to GPT-4o models.

Conclusion

The introduction of o1 Mini and o1 Preview represents a significant advancement in AI model capabilities, particularly in reasoning and specialized tasks. o1 Mini stands out for its exceptional performance in STEM fields and its cost-efficiency, making it an attractive option for organizations focused on these areas. Its speed and specialized capabilities in mathematics and coding set it apart from previous models.

On the other hand, o1 Preview offers a more balanced approach, excelling in a broader range of tasks and providing more comprehensive general knowledge. While it comes at a higher cost, its versatility makes it suitable for applications requiring diverse capabilities.

The choice between o1 Mini and o1 Preview ultimately depends on the specific needs of the user or organization. For STEM-focused applications where cost-efficiency and speed are crucial, o1 Mini is the clear winner. For more general-purpose applications requiring broad knowledge and versatility, o1 Preview may be the better choice despite its higher cost.

As OpenAI continues to refine these models, we can expect further improvements in both specialized and general capabilities. The AI community eagerly anticipates future developments that may bridge the gap between specialized and general-purpose models, potentially revolutionizing how we approach complex problem-solving and decision-making across various fields.

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