Latest ChatGPT Updates Explained: Memory, o3 & 04-mini, 4.1, Social Media Rumors

Hey, welcome to the Next Wave podcast. I'm Matt Wolf. I'm here with Nathan Lenz. And today we're going to try to do our best to demystify all of these recent launches with OpenAI, because they've released 4.5 and then 4.1 and then 04 and then O3, and it's just getting really, really confusing. So this episode is designed to break it all down for you, tell you which each of these models are good for, what they're not good for, and we'll even rank them from dumbest to artists at the end and tell you which ones to use for which things. So, without further ado, let's just go ahead and jump in and talk about all these recent OpenAI announcements. I think probably the best place to start is with this one right here, because this is the, probably the first piece of news in this sort of, you know, sprint that OpenAI is on of releasing news, which is that they just rolled out this memory feature in OpenAI. And to me, this is probably one of, like, the coolest, most valuable features they've rolled out. I found it really, really useful. I know. Nathan, before we hit record, you were saying something to the same effect of, like, out of everything, the memory is probably the coolest.

Yeah, I think. I mean, so it's funny, the. The team at Grok, they reached out to me about what should they build, like maybe like two months ago, and I was like, focus on memory. Nailed it first. Right, right. So unfortunately for elon Musk and Grok, OpenAI definite first. And I think long term, that's. That's how AI is going to get really useful for people. Because, like, people think of it right now as just ChatGPT, where you go in there and you copy and paste something in, maybe have it help you in some way. But eventually, like, these models are going to understand maybe what you want or what you want to accomplish better than you yourself. Understand that?

Yeah.

Yeah.

Well, I actually like the very first thing when this new memory feature rolled out was there was a button that says, do you want to try it? And I said, yeah, sure, let's try it. And it automatically pasted in this prompt. Describe me based on all our chats, make it catchy. This is what it said about me. I don't, I don't mind sharing mine. It says, you're Matt Wolf, a future Forward creator, a high trailblazer, and the Go to Tech Sherpa for over a half a million subscribers. You're not just riding the wave of innovation. You're helping build the surfboard. Your YouTube channel is a hub for creators, entrepreneurs and curious minds hungry for what's next in AI and tech. You break down the complex, spotlight the useful, and always bring the human angle, all while rocking a retro, futuristic vibe. Whether it's a short, punchy reel or deep dive 20 minute banger, your goal is always the same. Empower your audience to do more, create faster, and stay ahead off camera. You're a family guy with a white pup named Bowie, a deep love for camping, and a soft spot for the San Diego Padres. You've got a musician's soul, a builder's brain, and a storyteller's heart. Even when burnout hits or the algorithm plays rough, you keep showing up driven by purpose, not just metrics. You're not just documenting the future, you are part of shaping it. I was pretty flattered by that, so I don't mind sharing it.

Yeah, yeah, that. I mean, like, parts of that were kind of generic and then parts of it seemed like it was, you know, kind of personalized to you. I have a feeling I probably talked about more personal stuff with it because the stuff it said to me felt more personal than that. It said a lot of things that I did not tell it though, like, exactly like, it. It like kind of like understood things about me and what I. About how I feel about myself, about my accomplishments, my failures, things I want to accomplish before I die.

And it was stuff you didn't actually tell it. It sort of figured it out, some of it.

Some of it. And I was like, holy. You know, it's like it's connecting the dots. It's like, it's like, it's like understood my personality somewhat and the things that I get inspired by or that I want to do or that bother me or whatever, but it definitely connected some dots and said some things that I did not explicitly tell it, which was just, holy crap, that is. That's amazing.

Yeah. Yeah. And I really feel, for me, this one feels like pretty on par with like the various discussions I've had. Right. I have, you know, Talked about my YouTube channel a lot. Right. I use it a lot for, hey, I need an idea for this YouTube video. Here's the transcript. Help me come up with a title. All right. Help me come up with some concepts for thumbnails. Right. So I go to it a lot for like ideation around my YouTube channel. So it obviously knows a lot about the fact that I do stuff on YouTube.

It.

It has all the transcripts of my YouTube videos, because I always copy and paste them in and go, hey, how should I title this thing? It's kind of random that, like, the one sort of personal thing it picked out about me is that I have a dog named Bowie.

Right?

Not that I'm like, married with two kids or, you know, things like that, but just, I have a white dog named Bowie. I'm like, I don't actually remember telling you that, but it's true. So I'm sure it was in like one of my videos or something somewhere, right?

Yeah. I mean, mine was more personal and like, to the point where I didn't cry, but it made me feel emotional. Like reading it, I was like, that is crazy. And just imagine where that goes. Like, okay, that's that, like, like we always say that's the worst it's ever going to be.

Right, Right, right, right. And the more you use it, the better it's going to know about you. You know, the more it's going to know about you and the better response you're going to get on things like this.

We're totally going to have the thing that, like, you know, in the future, you know, you know, you know, pass away. You pass away, you'll have like a memory of who you were. It won't be perfect, but, God, it'll probably be like a 90% of the essence of, like, who you were as a person. And that, that is just shocking that, like, that, that technology is like, basically, it's almost there. It's like it's right there.

It's getting really close. And yeah, you know, this was, this was sort of just the first announcement. This was. This announcement came out on April 10th. Right. So this was sort of like the first in a series.

Small little announcement, like.

Yeah, they didn't even seem to make much of a big deal about it. I don't think, like, they even did a sort of live stream for this one. Everything OpenAI does a live stream about. And this one, they didn't even. They're just like, here, here's a new feature that we rolled out.

Well, they're talking about doing a social network and stuff now, which, if they do that memory is a core feature, that of actually understanding who the people are. Right. Yeah.

I mean, I don't. I. I actually haven't read too much into the whole social network thing. I just pulled up an article from Reuters about it. But, yeah, that's another announcement that has sort of bubbled up, is that OpenAI is working on an X, like social media Network, which is interesting, right? Because there's like a pretty big feud between Sam Altman and Elon Musk.

It makes sense, though. This is why I told the GROK guys, like that's why they should do it, is because they already have all that data about what people are sharing and what they're interacting, how they're interacting with people. And so that would be their advantage over OpenAI is that data.

Yeah, super interesting. We'll kind of keep an eye on how that one plays out. One of the other things that OpenAI has been doing is they've been releasing these new models, but they're also sunsetting a bunch of other models, right? So apparently GPT4 is going to be phased out on April 30th, and then also GPT 4.5, which up until this week was like, the newest model they released is also going to get phased out. They sent out an email to all of the OpenAI, you know, API users, or maybe it was everybody in ChatGPT, I don't know. But they, they sent out an email basically saying, we're going to phase out 4.5 because 4.1 is better and faster. Like, dude, OpenAI sucks at naming these.

Yeah, yeah, yeah. And they had said that they were going to solve that by doing GPT5, which would be like the all in one, the one, you know, the one model to rule them all kind of thing, where, like, you just talk to the one model and then behind the scenes it's routing you to whatever is the best model. Probably is what they're doing. But they didn't do it. They, like delayed it. They're like, oh, that's going to come out. No, sorry, we're going to have naming problems for a few more months. Like, give us like two or three more months and then. Yeah, yeah, that'll be solved. So I kind of Wonder, like, is 4.5, was it a failed run or are they just finding that it's so expensive that people don't know how to use it, so it makes more sense to improve upon it with some kind of new reasoning model or with the GPT5, have it part of that kind of stack of things that they might recommend?

I don't know. I mean, 4.5 has been my favorite model. When I've been using ChatGPT lately, I've been using 4.5 more than any other model.

But if I had to guess, I think it's the cost, right? Because the GPT 4.5, the cost of using it in the API was just, like, mind blowing. Like, nobody was using it because it was just way too expensive. So I think cost was probably the biggest factor. And supposedly, you know, they, they rolled out 4.1 inside of the API. So this is all super confusing, right? Because 4.5 is available in ChatGPT, but 4.1 is not available in Chat GPT, but it is available in the API.

And they were pushing this, like, good for coding, but I think they're pushing.

This one as the best one for coding.

Yeah, yeah. And so it's kind of confusing, but, like, then if O3 is out, I assume it's gotta be better at coding. So it's like, what's the use case? Or it's confusing.

Yeah. This one is available in the API. This is GPT 4.1 in the API. And they released 4.1, 4.1 mini and 4.1 nano. They outperform 4.04.0 mini. Um, let's see. Coding. It scores 54.6% on SUI bench verified, and it's an improvement over 4.0 and over 4.5. So apparently it's a lot better at coding than 4.5. But 4.5 wasn't good at coding in the first place. It was more sort of like, it felt more like human, like when you were chatting with it, I guess. But it wasn't really a model that was good with, like, logic and coding. But they did put out this, like, graph, which is intelligence based on multilingual mmlu, massive multitask language understanding. So this one's more of like, a general benchmark of just, like, intelligence. So we can see that GPT 4.1 nano, the latency, that's the speed. Right. So, like, how fast from the time you give it the prompt to, you get your response. So GPT 4.1 nano is super fast, but not the smartest mini is pretty smart. Smarter and faster than 4.0 mini. And the new full GPT 4.1 is about the same speed as 4.0, but slightly smarter. That's what I'm making from that journey.

Oh, my God. That's super confusing. So this is why they need the GPT5. It's interesting. They must have really realized, like, you do need different models for different use cases. And so there's like, well, for now, let's just keep giving them different crazy names. But then we'll have to make some kind of smart router, hopefully.

Well, and again, I think, like, their ultimate goal is you enter a prompt and then it chooses for you the best model to use. Right?

Like, yeah, well that's what GPT5, they've already said that's what it's going to be.

Okay, yeah, yeah, that's kind of the goal that they're trying to get to, you know. So SWE Bench, this is basically how good it is at coding. I believe this is the one where it goes on GitHub and tries to find like bugs that need to be fixed and how good is it at fixing them or something like that. Yeah, given a code repository, an issue description must generate a patch to solve the issue. So GPT 4.1 is way up here. But one thing I've noticed IS GPT and OpenAI has completely stopped comparing themselves to like external models. Like, you Notice how Gemini 2.5 got on here? Notice how Claude 3.7 is not on here. We don't know how this compares based on this graph to models that aren't OpenAI's models.

Right, right. Yeah. And who knows with the coding too. Like things have changed a lot in the last month. All of a sudden, like Google took over coding. Like Claude was like in a huge lead forever. Then they released 3.7 which seemed good, but they kind of got over ambitious because they would try to do tons of things for you and seem to be making more mistakes than 3.5 did.

And then Google came out with like 2.5 Pro, their Gemini model. And that's just been amazing. Like, like people haven't talked about that enough. Like Google has taken over coding with AI in the last month. I think most people probably don't realize that, but like that has happened in the last month.

Yeah, yeah, no, that's true. And I mean I still do quite a bit of coding. I've kind of been using Windsurf a little more than anything. A little more than cursor, really. Um, and yeah, I've been pretty much using Gemini 2.5 the most. And every once in a while I get hung up and I'll go to Claude and be like, well, can Claude solve it? And sometimes Claude can solve random stuff that Gemini can't. But I would say like 95% of my coding now is done with Gemini 2.5, which will be interesting because now OpenAI just released O3 and 04 mini, which this new O3 model is their most powerful model. But they also have O4, which is a bigger number than O3, but not as powerful as O3.

And you know, Sam Albin had said a few things about these models. Maybe like a month or two ago, saying, like. Well, more recently he said the benchmarks you saw for O3 were actually. We found some ways to improve upon the model more than we anticipated. So it's actually better than what we showed. But also in the past, he hinted at O3 Pro being amazing. And like you said off camera, maybe they're gonna O4 is O3 Pro. Maybe.

Maybe. Yeah. I'm not sure. Yeah. Or maybe O3 Pro might be what they launch as GPT5.

Yes. Or O3 Pro could be like in a week or two and it's only for the professional users or something. Yeah.

This O3 is their current most powerful model that we have access to. It's available to both Pro and Plus users. 04 Mini, I believe, is a faster, less expensive model, but still a very impressive model. We could kind of look at some of the charts that they show here. So they actually had another chart in their video that they're not showing here. But you can see that, like their 04 mini with no tools scored 92.7 on competition math. And they're. Oh, three with no tools scored 88.9. So when it comes to math, I guess 04 mini is better than O3. But then they, they showed this other chart in their launch video which showed O3 with Python and it got like a 99.5% or something crazy like that on the competition math. Basically, like acing it.

Yeah, yeah. That's why they had to have something like GPT5. Like, they're going to have to have like one smart router to like. Because all these models are good at different things. And it's, it's, it's. And some of it, you discover it over time. Like, some of it, I'm just like, you learn that like, oh, this model is just slightly better for this one thing. Yeah, yeah, yeah.

So we can see here that like, O3 and O4 mini, like, when it comes to competition, code here are like, pretty equal.

And then down here, the PhD level science questions. O3 is actually better at that than O4 mini, you know, but O4 mini is better at math, but not as good at science.

How big is the jump in General from like 01 to 03?

So we've got the estimated inference cost on this axis here. And then this is the math benchmark here. And we can see oh3 mini here, like, you know, is the lowest cost, but also didn't score as well. Where you've got 04 mini high on math here, pretty expensive comparatively. But also, you know, really smart. And then we can sort of see it in comparison here to 03, which is not as good, but it's not showing like the jump from like 01 Pro to 04, which is kind of frustrating.

Yeah, well, I mean, yeah, I think, I think oh, oh, three Pro be the more comparable there for a one Pro.

But then here we can see when it comes to graduate level Google proof. So basically grab graduate level questions that you can't just Google and answer for is essentially what that means. So on that benchmark, O3 mini actually performs about the same as 04 mini high, which is interesting.

Okay, so the DPQA is actually physics, by the way. So it's like physics questions.

Okay.

Like, yeah, hard questions.

Yeah, yeah. So cost performance. 01 and oh, three. Okay, so here we go. So here's. Okay, so here we can see this is math. Ame aime is math questions. Right. So we can see on math,03 for inference cost is down here. Oh 3 high is way up here. And the inference cost is like way cheaper than 01 Pro, which I believe is the same as Owen high.

Yeah.

I don't know why they're using different terminology. I think 01 high is 01 pro.

Yeah. But I think. Remember when we talked about when reasoning models first came out, I think when we were out in Boston.

We talked about how things were going to speed up now that there was this new paradigm where it wasn't just throwing more data at it, but you also could throw more compute power. And so we probably would see things improve dramatically faster. It feels like we're now seeing that because instead of the model getting, you know, twice as good in like, you know, two years, it's like now it's like what, like in three months or something?

Yeah. Oh, yeah. The amount of time between like each of these new releases is just like so fast or compressing.

Yeah, yeah, yeah.

But I mean, here's one that's really impressive. That same GPQ A here we could see like, here's the curve of O3. Look at where O1 Pro is basically down here. The cost is like the highest possible cost and it's dumber than 03 Low model or about on par with the O3 Low model here. And the 03 High is still cheaper than maybe slightly cheaper than 01 Medium. But like, look at the jump in intelligence way up here. It's pretty wild. The other day I used ChatGPT to sort through the latest AI news and tell me what order to talk about them in my YouTube videos and, and I was honestly surprised at how spot on it was. One of the biggest tips I give to people still building their confidence with ChatGPT is simple. Just start throwing prompts in and see what can do. Now to help you get rolling, HubSpot put together a free guide with over 100 prompts you can start messing with right now. Trust me, it's going to help you unlock some serious potential. You can grab it in the link below. Now back to the show. So, I mean, the speed at which these leaps are happening is pretty crazy.

Yeah, I think this is, you know, when we first started the show we were talking about like how big a change this was and I think people probably thought that was hype and it's actually happening now and I think people still don't understand. Sam Altman was interviewed at TED the other day.

Oh yeah, I saw that.

Yeah, yeah, I think he said that they have 500 million weekly active users now. And then the TED guy said backstage, you told me that your numbers doubled in a lot in the last month since the whole Ghibli thing came out. And he was like, that was supposed to be off record. But yeah, it's going well. I mean, so possibly OpenAI is what in the ballpark of maybe 700 plus million users? I mean that is just. We've never, Silicon Valley has never seen this before. And it's so wild that Sam Alma used to run yc like the big incubator for Silicon Valley, but he ends up producing the biggest startup of all time, possibly.

I wonder why he would want that to be off record. You know, that's like, that's something that would probably attract investors pretty quickly to know those.

Yeah, but I think he's, he's, you know, he's really intelligent. He's in, he is in a game with Google and, and Grok and Anthropic and everyone of like there's something you want to hype things up, but also you have to keep some cards secret. Right? Like you don't you want them to know exactly everything. And there's probably some misdirection and all kinds of stuff going on. But yeah, it's wild how fast this stuff is improving. And one thing that I found interesting is in the interview he alluded to this being possibly like the most pivotal year for AI, like basically saying. And he's also kind of like saying the best is yet to come kind of thing. And also talking about the next big thing is scientific discoveries and the biggest talk on X over the last week that I've seen is in some of them were even shared. Like, there was like, positive things being said by scientists too. Kind of alluding to this being possibly true through is that they've had early access to the new OpenAI models and possibly some new discoveries have been made, or at least experiments that they were not able to come up with that are now helping them possibly discover new things in science. So possibly this is like having like really, really material impact on science for the first time ever.

In fact, I actually let me pull up an article, I was actually reading this earlier. Yeah, it's on the information here. OpenAI's latest breakthrough AI that comes up with new ideas. If the upcoming models, dubbed O3 and 04 Mini, perform the way their early testers say they do, the technology might soon come up with novel ideas for AI customers on how to tackle problems such as designing or discovering new types of materials or drugs that could attract Fortune 500 customers, such as oil and gas companies and commercial drug developers, in addition to research lab scientists. The apparent improvements highlight the benefit of AI models focused on reasoning, which the ChatGPT maker debuted in September. But, yeah, basically saying that these new models, the people that got early access, have been saying, like, this is helping us design and discover new materials and drugs, which is like, that's kind of the holy grail of what people want AI to do.

Yes, yes. It looks like we're already there and we've just like scratched the surface of what this new paradigm with reasoning models can do. Like, there's no clear issues where it's not gonna be able to scale up, at least for several years. Maybe the future will be like, okay, we've kind of reached the limit of this, or it can slightly get better, but it seems like the next several years it's gonna keep accelerating and possibly revolutionizing science. It's like just. It's exciting.

Yeah. And one of the things about these new models that we haven't even touched on yet is that they're all being built in sort of, they're all being built multimodal. Right. So, like, they're theoretically, you can give them videos, you can give them audio, you can give them text, you can give them all the modalities, images, anything, and it will actually be able to understand what's going on within those. But also they're getting, they all have search now and they're all getting the ability to use tools. And so this chart I found pretty interesting. This is one that they showed in their, their live stream, but they didn't actually put on their website was that. You can see that when they gave 04 mini tool use and it was using Python to help with the math, it scored 99.5 on the competition math. So, like, basically acing competition math when you give it access to be able to use tools. Like, it's, it's getting to that point where, like, these benchmarks aren't good enough anymore. We need new benchmarks for, like, can AI, like, find new discoveries for us? Like, how do we make those kinds of benchmarks?

Right, yeah, it's all, it's, it's, it's getting wild. I, I think really, you know, and we're, we're getting more and more to a situation too. Like, when O1 came out, it took people a while to realize how good it was or, like, what it meant.

Yeah, yeah. We're entering completely new territory that nobody's been in yet. And even all the people that are trying to predict when things are going to happen or what's going to happen next are all just making predictions. Like, they don't even necessarily know what's coming or where.

Yeah, I've been preaching this for a while, but, like, I really feel like major corporations are not taking this seriously enough. Like, I think people don't realize how smart Elon Musk has been in this area where he's like, really, like, made things more lean and, like, move fast kind of thing. Every big company should be doing that because otherwise, how do you survive in an environment where things are dramatically changing?

Yeah, yeah. Did you see Toby? Toby Lutke or Lucky's statement from Shopify?

Yeah, yeah.

I mean, he's basically saying what you said, but, like, the big point that he made is if you guys want to hire anybody else in Shopify, you must prove that what you're hiring for can't be done with AI first. If you can prove I cannot do it, then okay, you can make the hire. But you must prove to me that I can't do it first.

Right. And it's also super clever because he's also kind of like, baking in AI into the culture of the company where it's like, look, if you're involved in the company, you have to be thinking about how you could be using AI to make the company better.

Yeah, right.

Like you. Because otherwise, how could you do that test if you're not, like, actually using AI and like, actively understanding what it can do?

And I don't think he's coming from a place of, like, AI is going to replace all of you. I think he's coming from a place of like, this company can be so much more efficient and so much better and get things done so much more smoothly if we're all leveraging AI together.

He's talking about like an AI first company. Like, even. Even though they're a large org restructuring already to be an AI first company. And most companies are not realizing this. I mean, I, I think like, like almost all major companies should be reorganizing right now, ahead of time. But, you know, like, people always, you know, they're more reactive than proactive. Like, especially big organizations, like, all the companies, they will realize this like five or ten years from now, and then some of them will not survive because of that. But, yeah, it's gonna be a wild time.

Yeah, well, so I want to bring this one home with, with this. So I actually asked OpenAI's deep research to sort of break down all of the models, like, help get past the confusion, do the deep research on which models are good at what, and then give me like a ranked order of basically which one is the dumbest to the smartest of all of the available models. Right now it actually took, let's see, 16 minutes for even ChatGPT to figure out its own dang models with how confusing it all is. But here's the breakdown. Let me kind of scroll down, because they did sort of rank order them here. So GPT 3.5 is great at basic conversations, but substantially lower reasoning and knowledge than the others. Then GPT4, which came out in March 2023, was a big leap from 3.5. And then you have GPT4 Turbo GPT4O, which apparently are sort of tied. Then you have GPT 4.1 Nano, which is one that came out this week, which is a very small but surprisingly capable model. 80% of GPT4's ability, basically. Then you have GPT4.1 4.1 Mini, slash GPT4O. So GPT 4.1 Mini was one that came out this week. GPT4O is the one that's sort of been the default model for a while inside of ChatGPT. But GPT4.1 mini, it says, matches or exceeds GPT4O's intelligence. So both are kind of tied. Then you have GPT 4.5, which was the one that they codenamed Orion. GPT 4.5 was one that's been available for Pro User or for. Was it Pro Users plus Users? I get all the names mixed up. I know it's been available in the $200 a month plan, I can't remember if it was available in the $20 a month plan.

But that one's been one that was sort of more human. Like, I guess it's good at writing stories, good at when you just want to have like a chat with an AI. That was the one that I always felt like was the best at having like a very human like conversation. Then you have OpenAI's 01. This was their first reasoning model where it actually sort of thought through after you gave it the prompt. And so during inference it sort of did that sort of chain of thought thinking. This was the first model we saw that was doing that. Then you have 04 mini, which was, I believe one that also came out this week, is a little bit better than just the standard 01. So it's a new efficient reasoning model. When run in high compute mode, it's extremely capable, likely outperforming 01 and approaching the top models in STEM benchmarks. Then you have GPT 4.14 full, which is another one that came out this week, which is OpenAI's latest GPT model, only available in the API right now, not available in Chat GPT. And this one's more tuned for coding and following instructions. But this is why it's a little bit confusing because we can see GPT 4.1 is actually a smarter model than GPT 4.5. So even though the numbering scheme went backwards, it's actually a more powerful model. And then you have OpenAI 01 Pro, which for the longest time was OpenAI's top dog model. If you got into ChatGPT and you had the 200amonth plan, O1 Pro was the best of the best. It just kind of crushed anything you threw at it. It was really good at coding. Took forever to get into the API, but that was their best for the long time. For a long time. And then you have OpenAI03, which was also one that was just released this week. It is available in chat GPT. It's available both in Pro and Plus, so 20 and $200 a month plans. This one is their, their new best, most powerful model they've they're making available right now. That's OpenAI03. And then the this list says their most intelligent, best possible model you can use is O3 with tool use turned on. So allowing O3 to use tools like Python and things like that to help it with its, you know, math and coding and logic and things like that. When you use O3 with tools, it's. It's their best model. And then also GPT 4.1, they've also sort of tied with it depending on the use case. So insanely confusing.

Yeah, yeah, yeah. So thank you.

But this is the order it ranked it in based on all the deep research.

Yes. I mean, so thankfully, like, people won't have to worry about this soon. So, like, hopefully in like, two months, you won't have to worry about this GPT5. Hopefully it'll be out. It'll manage all that for you. You just talk to one model. But right now I think their descriptions actually are pretty good in line with what, you know, my experience. Like, I think there's like, three models people really would. The average people would use right now, like, 4. 0. That's what most people would use. Like I said, that model keeps getting better. Like, yeah, I'm not sure if you're.

Just using ChatGPT free. That's what you're using. You're using 4.0.

Yeah, 4O is great. It just kept getting better. They had really, like, made a big fuss about it, but it seemed to have just kept getting smarter in some way. I don't think that that's entirely reflected in the benchmarks. 4.5 still seems to be the best for writing. So if you're wanting to edit something or write something, 4.5 is the best.

And then now that one's also getting phased out. So use it while you can.

Use it while you can. I think. I think it'll still be there in five if I had to guess behind the scenes. And then O3, which I haven't used yet. But based on the benchmarks and my understanding how the models work, I would assume that's going to be the best. If you have any complicated questions, like if there's something that you're, you know, that you're thinking like, oh, the model might give me too surface level of an answer. It's not taking the time to think it through. Because if you're asking something complex, you probably want to hand it to O3 and give it the time to really think through its response to you. I think that's probably what I would.

Imagine you're going to go to for coding as well.

Yeah, probably. So, like, I haven't, you know, haven't had a chance to test any of it with coding yet. I'm curious. I'm going to try it today, probably with like, repo prompt and then try it there.

There's one last thing that I, that we didn't actually bring up about the new models that they just released, and that's the context window. One of these models is actually a 1 million token context window.

He's like, is a real one. Like, I remember that was a part of the whole fiasco with Meta as well. It was like they said like 2 million context window and then apparently all the benchmarks, it would like, start to like, fall apart after like 128k context or something.

I was like, yeah, let me, let me see, let me look at here real quick. And we'll, we'll look at.

I don't know. I, I, I actually kind of trust OpenAI's word on this a little bit.

More than I trust. Yeah, yeah, yeah, yeah, me too. Me too. Because that was just ridiculous. Like, people tested it. It was like they were hyping up like 2 million context or 4 million or whatever it was they hyped up. And then, and then people tested it and as soon as it went beyond like 128k context, like, the model just like, became really dumb.

So one of these, I'm not actually not sure which one is the million token context window.

I would be surprised if they all are. That seems like it'd probably be like a benchmark they'd be aiming to hit. Now that seems like a, you know, Google's already there.

So gemini is what, 2 million? Llama 4 claims to be 10 million. Oh, that's what it was.

10 was like, yeah, way bigger number. Yeah.

But yeah, these context windows are getting to a point where, like, context length is not going to be an issue for very much longer.

Yeah.

And you're going to be able to plug in entire code bases and it's going to be able to read the whole dang thing.

Yeah, it is interesting that, like, Sam Altman kind of admitted he's like, well, he said, number one, like, people were, they were asking about, like, deep seeking. He's like, well, hasn't impacted our growth at all, so not really too worried about it. But also he was saying that, like, moving forward, like, it's probably more about the things they build on top of the models, because the models are only, he thinks they're going to continue to be in the lead, he said, but that lead is going to narrow and it's gonna be like a, a small lead in the future. So it's all about what they build on top of it.

So, yeah, that's pretty much a breakdown of all the OpenAI news that came out over the last few days. There was one Smaller update that's just like a quality of life thing. If you are generating Images Inside of OpenAI, they created this library page where you can see all the images that you've generated in just like one spot. You know, kind of cool quality of.

Life thing that they've added towards killing Mid Journey, possibly.

Yeah, very true.

Like, I'm gonna feel bad. Mid Journey.

Did you see the latest magazine cover?

No.

It's on the screen. Best AI YouTuber 2025.

Okay. Okay. It's official.

It's on Time magazine.

Yeah, it's right there. It's gotta be real. It's gotta be real for sure.

Yeah, we went off on a few little tangents, but, you know, hopefully we brought it all home by sort of showing you the ranking of intelligence. And I think, Nathan, you did a good job of saying, like, all right, these are the three models you're probably going to use.

Yeah.

So, you know, hopefully you found this informative and helpful. Trying to declutter your mind on all of these different open AI models, because it's still confusing to us. I mean, we're paying attention to it every day and we still get confused. So, you know, hopefully this helped a little bit. And thank you so much for tuning in to this episode. Hopefully you enjoyed it. If you like it, make sure that you subscribe, ideally on YouTube. That's where we're really trying to primarily grow the show. But if you prefer audio, we're available on Spotify and itunes and wherever you listen to podcasts. Thank you once again for tuning in and hopefully we'll see you in the next one.

Sa.