Yaacov Jacob, CPA (US)’s Post

GPT-o1 vs. GPT4o: It's important to understand that OpenAI's new o1 model is not necessarily better than GPT4o, but designed for different purposes. Let me explain: GPT-o1 - with its "advanced reasoning capabilities" - is a major breakthrough for tackling tasks that LLMs weren't so good at before: math, temporal understanding, logic - complex things where you need to think through something slowly, in steps. However, GPT-o1 isn't necessarily better across all fronts. Interestingly, it can perform worse in areas where LLMs were typically quite strong. Code completion, for example: As you can see on this benchmark table, o1 ranks behind Claude-3.5 Sonnet, and even behind GPT4o! (Same for creative writing, but that's just my anecdotal evidence). At the same time, GPT-o1 is ALWAYS more expensive than anything else because it generates more output - called reasoning tokens - before arriving at an answer. Clearly, this isn't something you want to have an easy conversation with. Most chatbot use cases won't work. Instead, GPT-o1 seems to work EXTREMELY well in "here's everything I know, process this carefully, and whenever you're ready get back to me with an answer–oh also tell me why" scenarios. As AI becomes more advanced, knowing which model to use for different business applications will become a key skill. GPT-o1 may not be the right tool for every job, but in the right situation, it could be a game changer for use cases that were previously pretty much impossible.

GPT-o1 vs. GPT4o: It's important to understand that OpenAI's new o1 model is not necessarily better than GPT4o, but designed for different purposes. Let me explain: GPT-o1 - with its "advanced reasoning capabilities" - is a major breakthrough for tackling tasks that LLMs weren't so good at before: math, temporal understanding, logic - complex things where you need to think through something slowly, in steps. However, GPT-o1 isn't necessarily better across all fronts. Interestingly, it can perform worse in areas where LLMs were typically quite strong. Code completion, for example: As you can see on this benchmark table, o1 ranks behind Claude-3.5 Sonnet, and even behind GPT4o! (Same for creative writing, but that's just my anecdotal evidence). At the same time, GPT-o1 is ALWAYS more expensive than anything else because it generates more output - called reasoning tokens - before arriving at an answer. Clearly, this isn't something you want to have an easy conversation with. Most chatbot use cases won't work. Instead, GPT-o1 seems to work EXTREMELY well in "here's everything I know, process this carefully, and whenever you're ready get back to me with an answer–oh also tell me why" scenarios. As AI becomes more advanced, knowing which model to use for different business applications will become a key skill. GPT-o1 may not be the right tool for every job, but in the right situation, it could be a game changer for use cases that were previously pretty much impossible.

GPT-o1 vs. GPT4o: It's important to understand that OpenAI's new o1 model is not necessarily better than GPT4o, but designed for different purposes. Let me explain: GPT-o1 - with its "advanced reasoning capabilities" - is a major breakthrough for tackling tasks that LLMs weren't so good at before: math, temporal understanding, logic - complex things where you need to think through something slowly, in steps. However, GPT-o1 isn't necessarily better across all fronts. Interestingly, it can perform worse in areas where LLMs were typically quite strong. Code completion, for example: As you can see on this benchmark table, o1 ranks behind Claude-3.5 Sonnet, and even behind GPT4o! (Same for creative writing, but that's just my anecdotal evidence). At the same time, GPT-o1 is ALWAYS more expensive than anything else because it generates more output - called reasoning tokens - before arriving at an answer. Clearly, this isn't something you want to have an easy conversation with. Most chatbot use cases won't work. Instead, GPT-o1 seems to work EXTREMELY well in "here's everything I know, process this carefully, and whenever you're ready get back to me with an answer–oh also tell me why" scenarios. As AI becomes more advanced, knowing which model to use for different business applications will become a key skill. GPT-o1 may not be the right tool for every job, but in the right situation, it could be a game changer for use cases that were previously pretty much impossible.

GPT-o1 vs. GPT4o: It's important to understand that OpenAI's new o1 model is not necessarily better than GPT4o, but designed for different purposes. Let me explain: GPT-o1 - with its "advanced reasoning capabilities" - is a major breakthrough for tackling tasks that LLMs weren't so good at before: math, temporal understanding, logic - complex things where you need to think through something slowly, in steps. However, GPT-o1 isn't necessarily better across all fronts. Interestingly, it can perform worse in areas where LLMs were typically quite strong. Code completion, for example: As you can see on this benchmark table, o1 ranks behind Claude-3.5 Sonnet, and even behind GPT4o! (Same for creative writing, but that's just my anecdotal evidence). At the same time, GPT-o1 is ALWAYS more expensive than anything else because it generates more output - called reasoning tokens - before arriving at an answer. Clearly, this isn't something you want to have an easy conversation with. Most chatbot use cases won't work. Instead, GPT-o1 seems to work EXTREMELY well in "here's everything I know, process this carefully, and whenever you're ready get back to me with an answer–oh also tell me why" scenarios. As AI becomes more advanced, knowing which model to use for different business applications will become a key skill. GPT-o1 may not be the right tool for every job, but in the right situation, it could be a game changer for use cases that were previously pretty much impossible.

GPT-o1 vs. GPT4o: It's important to understand that OpenAI's new o1 model is not necessarily better than GPT4o, but designed for different purposes. Let me explain: GPT-o1 - with its "advanced reasoning capabilities" - is a major breakthrough for tackling tasks that LLMs weren't so good at before: math, temporal understanding, logic - complex things where you need to think through something slowly, in steps. However, GPT-o1 isn't necessarily better across all fronts. Interestingly, it can perform worse in areas where LLMs were typically quite strong. Code completion, for example: As you can see on this benchmark table, o1 ranks behind Claude-3.5 Sonnet, and even behind GPT4o! (Same for creative writing, but that's just my anecdotal evidence). At the same time, GPT-o1 is ALWAYS more expensive than anything else because it generates more output - called reasoning tokens - before arriving at an answer. Clearly, this isn't something you want to have an easy conversation with. Most chatbot use cases won't work. Instead, GPT-o1 seems to work EXTREMELY well in "here's everything I know, process this carefully, and whenever you're ready get back to me with an answer–oh also tell me why" scenarios. As AI becomes more advanced, knowing which model to use for different business applications will become a key skill. GPT-o1 may not be the right tool for every job, but in the right situation, it could be a game changer for use cases that were previously pretty much impossible.

GPT-o1 vs. GPT4o: It's important to understand that OpenAI's new o1 model is not necessarily better than GPT4o, but designed for different purposes. Let me explain: GPT-o1 - with its "advanced reasoning capabilities" - is a major breakthrough for tackling tasks that LLMs weren't so good at before: math, temporal understanding, logic - complex things where you need to think through something slowly, in steps. However, GPT-o1 isn't necessarily better across all fronts. Interestingly, it can perform worse in areas where LLMs were typically quite strong. Code completion, for example: As you can see on this benchmark table, o1 ranks behind Claude-3.5 Sonnet, and even behind GPT4o! (Same for creative writing, but that's just my anecdotal evidence). At the same time, GPT-o1 is ALWAYS more expensive than anything else because it generates more output - called reasoning tokens - before arriving at an answer. Clearly, this isn't something you want to have an easy conversation with. Most chatbot use cases won't work. Instead, GPT-o1 seems to work EXTREMELY well in "here's everything I know, process this carefully, and whenever you're ready get back to me with an answer–oh also tell me why" scenarios. As AI becomes more advanced, knowing which model to use for different business applications will become a key skill. GPT-o1 may not be the right tool for every job, but in the right situation, it could be a game changer for use cases that were previously pretty much impossible.