⚡️GPT 4.1: The New OpenAI Workhorse

**Alessio** (0:07)
Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Decibel, and I'm joined by my co-host, Swix, founder of Small AI.

**Swix** (0:16)
Hey, and today we have a returning guest, as well as the new friends. Welcome, Michelle and Josh.

**Alessio** (0:21)
Hey there.

**Swix** (0:23)
Both of you work on the, I guess, Michelle, I think you used to introduce you as manager on the API team. It seems like you've changed your role since we last talked on the podcast.

**Michelle Pokrass** (0:33)
Yeah, now I lead a team on the research side, specifically in post-training.

**Swix** (0:38)
Yeah. And Josh, you are also on post-training. Yep.

**Josh McGrath** (0:41)
I'm a researcher on Michelle's team.

**Swix** (0:43)
Yeah. And I just found an interesting commonality you guys have. You're also both from Waterloo, continuing the tradition of extremely correct engineers.

**Michelle Pokrass** (0:50)
Oh yeah. We talked about that last time. That's right.

**Swix** (0:54)
Okay. So we're gathering to talk about GPC 4.1. You launched it. I mean, we got a little preview and it was a little bit rumored, right? It was pre-released, I guess, with OpenRouter as Quasar Alpha. And then it was also an Optimus version. And I think people are trying to figure out, like, why are we going back from 4.5 to 4.1? You know, there's a whole bunch of other things. But like, what are the headline facts, I guess, you guys want to emphasize about 4.1?

**Michelle Pokrass** (1:20)
Yeah, I'll just say we released three new models today. Gpt 4.1, Gpt 4.1 Mini and Gpt 4.1 Nano. And the real focus on these were just making the models that were great for developers. So, we improved instruction following, coding, and shipped our first 1 million context models.

**Swix** (1:38)
Josh, anything to add? I don't know if there's anything else that people should really... that are like, sort of in the fine print.

**Josh McGrath** (1:45)
No, I think the only thing that I would touch on maybe twice is that there's actually a new model in the lineup, Nano, which is even faster for developers that are making, you know, low latency applications.

**Alessio** (1:57)
And cheaper. What's the, any fun story behind the code names? Or, you know, I got the strawberry hat as another fun time in the lower open AI.

**Michelle Pokrass** (2:08)
Yeah, yeah, we really wanted to get as much developer feedback as possible on this model to make sure it worked well in the real world. And so we tested it kind of through OpenRouter and it was super cool to see people latch on to the names and get the theories going. But the feedback we got from there was super helpful.

**Swix** (2:28)
Yeah, yeah, it's not even like the name. It's more about just like the API shape. Once we saw like Chag Kumpul, it was like very obviously OpenAI.

**Michelle Pokrass** (2:37)
Yeah, it's a good note.

**Swix** (2:40)
Yeah, but like, I mean, okay, is there like an emphasis on stars? Like what inference were we supposed to draw from, you know, quote unquote, supermassive black holes?

**Josh McGrath** (2:50)
I don't think there's anything really to draw from there.

**Swix** (2:52)
Okay, they're just cool.

**Michelle Pokrass** (2:55)
You know, they make you think of cool concept.

**Alessio** (2:58)
The vibes are good. The vibes are good.

**Michelle Pokrass** (3:00)
You know, yeah.

**Swix** (3:02)
The other thing about the examples, we're just mining for lore here, right? The interesting animal comes up a few times on the live stream and on the blog post. What's up with Tapirs? Who likes Tapirs here?

**Michelle Pokrass** (3:11)
Yeah, our team is just a super big fan of Tapirs. So they just happened to work their way into a lot of our content. Okay, cool.

**Alessio** (3:22)
Yeah, go ahead.
I think the first thing that we just want to run through is obviously the 4.1 to 4.5. I think that's the first thing that everybody was maybe confused about. So I don't know, you're demarcating 4.5. It sounds like 4.1 is just like a kickass model and the 4.5 size, maybe it's not as good of a fit. That was just a research preview. So yeah, I don't know, whatever you want to say to address that. I think it's something we've seen come up also in the Discord.

**Michelle Pokrass** (3:50)
Yeah, totally. Okay, naming is really hard and we've tried to make this as less confusing as we can, but nothing's perfect. Basically, the way we got here is that Gpt 4.1 is a pretty big improvement over the 4 line and we really wanted to signify that. However, it's a model that's much smaller and cheaper than Gpt 4.5 and as a result doesn't achieve the same like Amy or other intelligence evals. So it doesn't beat 4.5 on all of the evals and so we didn't think it made sense to increment beyond 4.5. But we do think for most developers, they can kind of replace a lot of their 4.5 usage with 4.1.