/** * file: chatgpt_karbytes_10march2025.txt * type: plain-text * date: 11_MARCH_2025 * author: karbytes * license: PUBLIC_DOMAIN */ The following is a plain-text transcript of a conversation between karbytes and ChatGPT-4o which took place on 09_MARCH_2025 at approximately 5:30PM Pacific Standard Time and pertains to karbytes inquiring about a newly-available model of ChatGPT named ChatGPT-4.5 and how it compares to other ChatGPT models. * * * karbytes: Who currently has access to ChatGPT-4.5? ChatGPT: As of March 9, 2025, access to GPT-4.5 is structured as follows: - ChatGPT Pro Subscribers: Users subscribed to the ChatGPT Pro plan, priced at $200 per month, have immediate access to GPT-4.5. - ChatGPT Plus Subscribers: Subscribers to the ChatGPT Plus plan ($20 per month) are currently receiving access to GPT-4.5. - ChatGPT Team Plan Users: Users on the Team plan also have access to GPT-4.5. - Developers: Developers can access GPT-4.5 through OpenAI's API, though it is noted that the model is more compute-intensive and expensive compared to previous versions. ​ OpenAI has not yet announced plans to make GPT-4.5 available to free-tier users. karbytes: Is ChatGPT-4.5 capable of doing everything that ChatGPT-4o can? ChatGPT: Yes, GPT-4.5 encompasses all the capabilities of GPT-4o and introduces several enhancements: 1. Enhanced Language Understanding: GPT-4.5 exhibits improved comprehension of context and subtext, enabling more natural and nuanced interactions. ​ 2. Reduced Hallucinations: The model has a lower tendency to produce inaccurate information, enhancing reliability. ​ 3. Improved Creativity: GPT-4.5 demonstrates greater creativity in tasks such as writing and problem-solving. ​ 4. Broader Knowledge Base: The model has been trained on a more extensive dataset, providing a wider range of information. ​ However, GPT-4.5 does not employ chain-of-thought reasoning, which is characteristic of OpenAI's o-series models. This means that while GPT-4.5 excels in language fluency and general knowledge, it may not perform as effectively as models like o1 or o3-mini in tasks requiring detailed, step-by-step logical reasoning. ​ reddit.com+4datacamp.com+4help.openai.com+4 In summary, GPT-4.5 retains all functionalities of GPT-4o, with notable improvements in language understanding and reliability, but it may not be the optimal choice for complex reasoning tasks.​ karbytes: Rank (in order) the best and the worst ChatGPT models. ChatGPT: As of March 9, 2025, OpenAI's ChatGPT models can be ranked based on their performance, cost-effectiveness, and specialized capabilities. Here's an ordered list from best to worst, considering various factors: 1. o1-preview: This model excels in complex reasoning tasks, particularly in STEM fields. It offers a large context window of 128,000 tokens and high output quality. However, its higher cost and increased latency make it more suitable for specialized applications. 2. o1-mini: Optimized for coding and STEM applications, o1-mini provides a balance between performance and cost. It maintains a large context window and delivers faster response times compared to o1-preview. 3. GPT-4o: Known for its versatility, GPT-4o performs well across various tasks, including research, image generation, and coding. It offers a substantial context window and faster response times, making it suitable for general-purpose use. 4. GPT-4o mini: A cost-effective version of GPT-4o, this model provides reasonable performance for less demanding tasks. It shares the same context window size but with reduced output quality, reflecting its lower cost. 5. GPT-3.5 Turbo: While being an older model, GPT-3.5 Turbo remains relevant due to its cost-effectiveness and speed. It has a smaller context window and may lack the nuanced understanding of newer models but is suitable for straightforward tasks. It's important to note that the "best" model depends on specific use cases. For complex reasoning and STEM-related tasks, o1-preview and o1-mini are preferable. For general-purpose applications, GPT-4o and its mini variant offer a good balance between performance and cost. GPT-3.5 Turbo is suitable for simple tasks where speed and cost are primary considerations. karbytes: You forgot to include ChatGPT-4.5 in that list. ChatGPT: Apologies for the earlier omission of ChatGPT-4.5 in the model ranking. Here's an updated ranking of OpenAI's ChatGPT models as of March 9, 2025, from best to worst, considering their performance, capabilities, and cost-effectiveness: 1. o1-preview: Excels in complex reasoning tasks, particularly in STEM fields, with a large context window of 128,000 tokens and high output quality. However, its higher cost and increased latency make it more suitable for specialized applications. 2. o1-mini: Optimized for coding and STEM applications, o1-mini provides a balance between performance and cost. It maintains a large context window and delivers faster response times compared to o1-preview. 3. GPT-4.5: Introduced in February 2025, GPT-4.5 offers enhanced language understanding, reduced hallucinations, and improved creativity. However, it does not employ chain-of-thought reasoning, which is characteristic of OpenAI's o-series models, making it less effective for tasks requiring detailed, step-by-step logical reasoning. 4. GPT-4o: Known for its versatility, GPT-4o performs well across various tasks, including research, image generation, and coding. It offers a substantial context window and faster response times, making it suitable for general-purpose use. 5. GPT-4o mini: A cost-effective version of GPT-4o, this model provides reasonable performance for less demanding tasks. It shares the same context window size but with reduced output quality, reflecting its lower cost. 6. GPT-3.5 Turbo: While being an older model, GPT-3.5 Turbo remains relevant due to its cost-effectiveness and speed. It has a smaller context window and may lack the nuanced understanding of newer models but is suitable for straightforward tasks. ​ It's important to note that the "best" model depends on specific use cases. For complex reasoning and STEM-related tasks, o1-preview and o1-mini are preferable. For general-purpose applications, GPT-4.5 and GPT-4o offer a good balance between performance and cost. GPT-3.5 Turbo is suitable for simple tasks where speed and cost are primary considerations.​ karbytes: Describe chain-of-thought reasoning and how it compares to ChatGPT-4.5's method of "reasoning". ChatGPT: Chain-of-Thought Reasoning vs. ChatGPT-4.5's Method of "Reasoning" 1. What is Chain-of-Thought (CoT) Reasoning? Chain-of-thought (CoT) reasoning is a method where a language model explicitly breaks down its reasoning process into multiple steps, similar to how a human would solve a complex problem in a step-by-step manner. This technique improves performance on tasks that require multi-step logic, such as: - Mathematical reasoning (solving equations, stepwise problem-solving) - Logical deductions (syllogisms, riddles, and structured inference) - Programming-related tasks (debugging, algorithmic reasoning) - Commonsense reasoning (understanding cause-and-effect relationships) Example of Chain-of-Thought Reasoning: Question: A bookstore sells three books for $10 each and two books for $15 each. What is the total cost? Chain-of-Thought Answer: - Three books at $10 each cost: 3 × 10 = 30 - Two books at $15 each cost: 2 × 15 = 30 - Total cost: 30 + 30 = 60 - Final Answer: $60 The explicit breakdown of the reasoning process makes it easier for the model to avoid errors, especially in logical or mathematical problems. 2. How Does ChatGPT-4.5 "Reason"? Unlike models that employ Chain-of-Thought reasoning (such as OpenAI’s o-series models like o1-preview and o1-mini), GPT-4.5 does not inherently generate step-by-step reasoning in the same structured manner. Instead, GPT-4.5: - Uses pattern recognition and probabilistic modeling to infer answers quickly. - Relies on past training data to generate responses that seem logically sound. - Does not explicitly "think" step-by-step but instead outputs an answer in a fluent, confident manner—often without showing intermediate steps unless explicitly prompted. 3. Comparison Example (GPT-4.5-style reasoning): Question: A bookstore sells three books for $10 each and two books for $15 each. What is the total cost? GPT-4.5 Answer: The total cost is $60. Unlike a Chain-of-Thought model, GPT-4.5 would typically provide the answer directly without showing intermediate calculations, unless specifically asked to "show steps." 3. Key Differences Between CoT Reasoning and GPT-4.5's Approach Feature | Chain-of-Thought (CoT) Models (e.g., GPT-4o, o1-preview, o1-mini) | GPT-4.5 Step-by-Step Explanations | Explicitly breaks down reasoning | Provides direct answers unless prompted Suitability for Complex Problems | Excels at multi-step reasoning | May struggle with deep logical problems Mathematical Accuracy | More reliable for multi-step calculations | Can make more errors without explicit reasoning Logical Deduction | Stronger in structured logic tasks | More prone to heuristic errors Speed | Slightly slower due to step-by-step nature } Faster but less explainable Transparency of Thought Process | Clearly shows how an answer is derived | Often skips intermediate reasoning 4. When to Use Which Approach? - If you need detailed reasoning, logic-based problem solving, or math-heavy tasks, a Chain-of-Thought model (e.g., GPT-4o or o1-preview) is preferable. - If you need quick, fluent responses with a focus on general knowledge or conversational tasks, GPT-4.5 is a solid option. Conclusion While GPT-4.5 provides improved fluency, creativity, and factual accuracy, it does not inherently perform step-by-step logical reasoning like models equipped with Chain-of-Thought prompting. For deep logical deduction, structured problem-solving, and mathematical accuracy, models like o1-preview or GPT-4o outperform GPT-4.5. However, GPT-4.5 remains excellent for fast, general-purpose interactions where stepwise explanation is not required.