GPT-4.1, every mention
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every year anyone Michelle Pokrass 19Shawn Wang 11Josh McGrath 4Pratyush Maini 3Will Brown 1Stefano Ermon 1Alexander Embiricos 1
Verbatim, from the transcripts: the passages where GPT-4.1 comes up
⏭️ Forward Deployed: Voice AI on what works in 2026
- ▶ 35:58 unnamed speaker Over GPT-Foto is 4.1, you know, the popular real-time models.
⚡️ Reverse Engineering OpenAI's Training Data — Pratyush Maini, Datology
- ▶ 9:44 Pratyush Maini And then four months after that, we noticed that the GPT 4.1 series is the first model where suddenly this, the response length of all the models had started to increase. 2 times in the scene
- ▶ 16:35 Pratyush Maini I think also what's interesting to me that the GPT-D-Fort.one series came about four months after the O-one data was available, so it's kind of interesting, like, how fast do Frontier Labs move?
[State of Post-Training] From GPT-4.1 to 5.1: RLVR, Agent & Token Efficiency — Josh McGrath, OpenAI
- ▶ 0:39 Josh McGrath Yeah, it's been wild, and like, you know, 4.1 was a non-thinking model, and then since then I, you know, we sort of switched into doing.
- ▶ 16:40 Josh McGrath I worked on long context, that was why I was on last, was for 4.1, where we, you know, I think, tenxed the, the effective context window for 4.1, and so, there'll always be some dance of, like, 3 times in the scene
⚡️Mercury: Ultra-Fast Diffusion LLMs — Estefano Ermon, CEO Inception Labs
- ▶ 17:03 Stefano Ermon So it's, it's comparable to GPT, 4.1 nano, cloud haiku, kind of like
Information Theory for Language Models: Jack Morris
- ▶ 40:57 Shawn Wang Uh, so Gemma three N is like a really good candidate right now because it's like a four B model that is like claimed to be better than Lama four and GPT 4.1, uh, according to, you know, certain arenas that shall not be named.
⚡️Multi-Turn RL for Multi-Hour Agents — with Will Brown, Prime Intellect
- ▶ 7:48 Will Brown GPT.
ChatGPT Codex: The Missing Manual
- ▶ 35:47 Alexander Embiricos Like for example, uh, recently we released GPT 4.1, like really good coding model.
GPT 4.1: The New OpenAI Workhorse
- ▶ 0:58 Shawn Wang Uh, ok, so we're, we're gathering to talk about GPT-C, uh, um, you, uh, launched it. 3 times in the scene
- ▶ 1:27 Michelle Pokrass Yeah, I'll just say we released three new models today, GPT-Fort.one, GPT-Fort.one mini, and GPT-Fort.one data, and the real focus on these were just making the models that were great for developers, um, so we improved instruction…
- ▶ 1:27 Michelle Pokrass Yeah, I'll just say we released three new models today, GPT-Fort.one, GPT-Fort.one mini, and GPT-Fort.one data, and the real focus on these were just making the models that were great for developers, um, so we improved instruction… 2 times in the scene
- ▶ 3:44 unnamed speaker I, I think like the first thing that, yeah, we just want to run through is obviously the 4.1 to 4.5. 10 times in the scene
- ▶ 4:55 unnamed speaker And then the many is strictly better than four or many. 2 times in the scene
- ▶ 5:02 Shawn Wang With the, with the nano, like, um, but like, we don't know if 4.1 is a distillation of 4.5 or there's, there's no relationship there. 2 times in the scene
- ▶ 16:11 Michelle Pokrass So, 4.1 is powering the API, whereas, uh, the enhanced memory is, is ChatGPT only.
- ▶ 20:22 unnamed speaker Um, so there's the instruction following section and this great prompting GPT for one models.
- ▶ 27:06 unnamed speaker Should I just use 4.1 and prompt it to do a channel thought? 5 times in the scene
- ▶ 28:12 Michelle Pokrass Then maybe you could drop down a 4.1 mini and save latency, or even nano.
- ▶ 28:12 Michelle Pokrass Then maybe you could drop down a 4.1 mini and save latency, or even nano.
- ▶ 30:13 Michelle Pokrass Um, yeah, there's kind of just a bunch of work streams that all coalesced around, uh, GBT. 8 times in the scene
- ▶ 32:15 Michelle Pokrass Um, so you can see, like, 4.1 mini is actually quite significantly better than four o mini, um, and not that far away from the old four o.
- ▶ 34:54 unnamed speaker Oh, I was gonna say, I think one, maybe small nugget there is actually, I think the, that 4.1 mini is really exciting on that front. 2 times in the scene
- ▶ 36:09 unnamed speaker I think one of the, uh, first off, I think that 4.1 is better at both of those things, uh, regardless of how it was actually trained. 4 times in the scene
- ▶ 36:49 unnamed speaker I think one of the things that was really funny with both, uh, the 4.1 mini and nano is we had some strange internal eval results and it turns out that actually the,
- ▶ 38:44 Shawn Wang Uh, for one, 4.1 only, and mini, 4.1 and mini only, and nano and future. 3 times in the scene
- ▶ 38:44 Shawn Wang Uh, for one, 4.1 only, and mini, 4.1 and mini only, and nano and future.
- ▶ 38:44 Shawn Wang Uh, for one, 4.1 only, and mini, 4.1 and mini only, and nano and future.
- ▶ 43:11 Michelle Pokrass So one clarification, um, which is that GPT, 4.1 mini is not cheaper than GPT four out. 2 times in the scene
- ▶ 43:18 Michelle Pokrass So not, it's not just like a blanket decrease in all the models, but however, 4.1 mini is cheaper than 4.1. 2 times in the scene