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[–]ComparisonMelodic967 57 points58 points  (4 children)

December 2025? Boo!

But good post

[–]New_Equinox 27 points28 points  (3 children)

Reality is often dissapointing

But hey, by then we'll have a lot of other models won't we

[–]dogesator[S] 11 points12 points  (1 child)

I wouldn’t call it disappointing personally. It’s just a difference in numbering but I’m sure that this GPT-4.5 that may be training right now is still using all that scaled up compute in the massive new supercomputer mentioned by microsoft, and still likely using all of OpenAIs newest techniques and research, potentially with a new type of interface paradigm as well, just like we experienced with the jump from story completion to back and forth conversations when GPT-3.5 was introduced.

I think GPT-4.5 may end up even beating many pessimists expectations of what they expect GPT-5 to be capable of, much like GPT-3.5 was beyond the scope of what a lot of AI doubters would have believed is possible at the time.

[–]sdmat 5 points6 points  (0 children)

Exactly, who cares what the numbers are - it's the model that matters.

[–]inquilinekea 1 point2 points  (0 children)

I mean, if December 2025 is *genuinely* PhD-lvl intelligence, then that's huge.

[–]GraceToSentienceAGI avoids animal abuse✅ 17 points18 points  (1 child)

Does that take into account the fact that:
-GPT-3 was released without the 6 month evaluation time like gpt-4 was
-Apparently !openAI train a new x point 0 version every 2 years (gpt 3 finished training in 2020 and gpt-4 2022)
-Does that take into account the ramping up of the competition and the very big increase of !openAI Employee count?

[–]dogesator[S] 14 points15 points  (0 children)

  1. Yes I considered that, but I think if anything GPT-5 may have an equal or possibly more safety evaluation period as GPT-4.

  2. The training gap between GPT-3 and GPT-4 isn’t perfectly 2 years, IIRC GPT-3 started training around March 2020 and GPT-4 was around June, so it’s about 27 months, but a possibly increasing period of safety evaluation times could account for an extra gap here, as well as a longer training period potentially happening for GPT-5.

  3. The 33 month gap extrapolation is just one data point but I think the stronger evidence for this is specifically the fact that mira murati implied specific capabilities specifically happening in a year and a half from now, and also the fact that the gap between model generations has grown or stayed the same between each model release since GPT-1 and has never shrunk between full model generation leaps.

  4. Yes I thought about the factor of competition increasing, but I think that will simply make OpenAI more incentivized to make GPT-5 even better than they originally planned to do while keeping release date the same by coming up with even better research advancements that they’ll incorporate into the future training run, but that doesn’t necessarily have anything to do with the release date. Because of GPU shipment timelines I think its much more likely they would decide to just keep GPT-5 release date the same and just make the model more advanced than expected on release date if they end up having more employees or better research advancements than expected, as opposed to keeping the planned model capabilities at a fixed point while just trying to get that level of capabilities as soon as possible.

  5. Yes I also had thought about increasing employee size, but there is a superlinear increase of employees already required for every model release, I think it’s a natural trend that GPT-5 would already require superlinearly more employees than GPT-4, even if they had 33 months gap after GPT-4.

GPT-2 had 5 authors GPT-3 had 31 authors GPT-4 had ~180 authors

If we assume that same labor requirement will be required for future models on this same multiplicative trend, then this would be about 1,080 authors that need to work on GPT-5, last official numbers I heard for OpenAI employee count is around 800, so they might be a little low but I don’t think that will delay the model release still for the same reason as I said before, I believe they will simply put whatever they can as possible towards a model with a fixed release date, as opposed to changing the release date to be later or sooner based on a changing variable of resources or research they have on hand. This is consistent with how would you would usually plan and work towards research and engineering within companies.

I think OpenAI may have indeed made more advanced research improvements since GPT-4 than they expected, but I suspect that they likely won’t necessarily make GPT-5 come sooner because of this, they’ll instead just make GPT-5 even more amazing while keeping the GPT-5 training and release schedule the same, especially since a ton of server build out schedules and GPU shipment schedules are likely already set up around mostly fixed training time in the future. Especially due to the limitations of when B200 GPUs start shipping in high volume.

[–]Eyeswideshut_91 18 points19 points  (3 children)

What makes me think there will be a release of some new model before the end of 2025 is the fact that such a long time span in such a competitive landscape would mean seeing their current models become completely obsolete in the meantime.

Claude Sonnet 3.5 has already been released. The Opus version will necessarily be better than Sonnet, establishing itself as the superior model and becoming integrated into the minds and workflows of many.

It seems really unreasonable to think that OpenAI could let a year and a half pass, in such a competitive environment, without releasing ANYTHING more powerful than what is currently available.

[–]dogesator[S] 6 points7 points  (2 children)

If you read everything I said you’ll see that I’m actually not even saying that they won’t release anything for a year that’s more powerful than what is currently available.

Quite the contrary actually, I’m specifically saying that they are training a new significantly better model with a new supercomputer right now called GPT-4.5 that we’ll likely get access to quite soon within a few months, and we might even see further improved versions of that too over the next 18 months before GPT-5 comes, like a GPT-4.5-turbo and different updated versions just like we had GPT-4-0613 and GPT-1106 etc.

GPT-3 to 3.5 was a pretty massive jump and I expect GPT-4 to 4.5 to be similarly impactful relative to eachother.

Edit: I misinterpreted the comment and thought you misunderstood my post and were disagreeing with me. Never mind haha.

[–]Eyeswideshut_91 7 points8 points  (1 child)

I agree.

In fact, my comment was not a contradiction to your post, which I upvoted, but an additional reflection on the competition as a further driving force that makes it really implausible that they won't release any model more powerful than 4o in the meantime.

[–]dogesator[S] 8 points9 points  (0 children)

Ah sorry, I see now I misinterpreted.

[–]Arcturus_LabelleAGI makes vegan bacon 9 points10 points  (0 children)

Appreciate the effort post! Nice

[–]Formal-Dentist-1680 7 points8 points  (0 children)

Great post! This also gels with Kevin Scott saying on May 31 that:

"If you think of GPT-4, and like that whole generation of models is things that can perform as well as high school students on things like the AP exams. Some of the early things that I’m seeing right now with the new models is like, you know, maybe this could be the thing that could pass your qualifying exams when you’re a PhD student." https://youtu.be/b_Xi_zMhvxo?si=lHpm7Uru7t8RcsPZ (Quote at 1:40)

GPT-4.5 would be part of "that whole generation of [GPT-4] models" while GPT-5 would be "the new models."

So the "early things that I'm seeing" are probably their experiments to confirm the scaling laws are still holding up before ordering a few billion dollars of B200s for GPT-5?

[–]FeltSteam▪️ 11 points12 points  (5 children)

I mean Sam Altman said GPT-6 would be around PhD level intelligence at that private Stanford event, so I think the timeframe Mira presented about PhD level intelligence around 18 months from now is more of a GPT-6 type model.

I think there is also more of a rush to get GPT-5 out there, so I think it is quite plausible to see a smaller gap between GPT-4 and GPT-5 then we saw between GPT-3 and GPT-4, like Q1 2025 or earlier.

I mean for all we know GPT-5 trained in January (120 days, 100k H100s or smthn like that) and they are distilling it to make a GPT-4.5 that will release relatively soon and they started training GPT-6 in May, but that is just speculation with little evidence behind it lol.

[–]dogesator[S] 9 points10 points  (0 children)

What’s interesting here is that Sam mentioned GPT-6 being PhD level in ALL areas, meanwhile Mira Murati mentioned models in 18 months having PhD level in just some areas.

[–]OmnipresentYogaPantsYou need triple-digit IQ to Reply. 1 point2 points  (0 children)

I know we're going full steam, but I doubt PhDs will degenerate THAT quickly.

[–]flying-pans 1 point2 points  (2 children)

I mean Sam Altman said GPT-6 would be around PhD level intelligence at that private Stanford event

Where did he say that in the event recording? At least from what I remember, he only said that GPT-6 will be smarter than 5 and he can imagine a world where they make general PhD-domain intelligence. So, essentially just the same general platitudes as before.

[–]FeltSteam▪️ 4 points5 points  (1 child)

No, not that one. There was the other private event that wasn't recorded as far as I am aware.

I think it was this one https://x.com/itsandrewgao/status/1783301236126847379

<image>

There was a summary from someone who attended, these were three of the dot points from that summary.

The summary/leak of this private event originated from someone in the YouTuber "AI Explained" private discord im pretty sure.

[–]flying-pans 2 points3 points  (0 children)

Ah yeah, that one. I don't recall the anon person ever posting solid evidence that they were actually at the private session or someone else who was def at the event also corroborating those points. The biggest thing, iirc, was 4o which was basically publicly known at that point, so not really a leak. The whole thing just struck me as more chicken feed.

[–]dogesator[S] 9 points10 points  (0 children)

TLDR; GPT-4.5 coming within the next few months.

GPT-5 potentially coming around December 2025 (hasn’t started training yet)

GPT-4.5 currently being trained on Microsofts new super computer, this is fairly consistent with a mistakenly uploaded blog post that OpenAI published in the past, as well as consistent with Mira Murati teasing that new frontier models are coming soon after the GPT-4o event. A December 2025 release date for GPT-5 would be consistent with the 33 month gap that we previously saw between GPT-3 and GPT-4, and this would also be consistent with some claims that Mira recently had made about PhD level intelligence potentially coming in "a year and a half", this is further consistent with the new B200 GPU supply not expected to ramp up until early 2025.

[–]UnfocusedbrainADHD: ASI's Distractible Human Delegate 3 points4 points  (0 children)

Great post!

[–]Formal-Dentist-1680 3 points4 points  (2 children)

Any guess what the headline-grabbing feature of GPT-4.5 could be? 

Mine is direct mouse & keyboard GUI control of Macs. So you just talk to the ChatGPT Mac app (using 4o's voice mode) while GPT-4.5 clicks and types on your Mac to complete actual work. Whenever it makes a mistake or goes off the rails, you "intervene" (ala Tesla FSD) by saying "no, no, not that, do this instead..." ect. Seems like that would be excellent RL-type data flywheel to train GPT-5.

Also, I think they need a flashy new interaction paradigm to catch the public imagination as opposed to better benchmark scores.

[–]dogesator[S] 3 points4 points  (1 child)

I fully agree, I was actually going to mention some things about interaction paradigms too but I didn’t want to make my post too long.

OpenAI officially registered the subdomain called “AgentChat” and I suspect this may be a significantly new and advanced interface paradigm that we see with GPT-4.5 similar to the jump from story completion to chat conversation paradigm from GPT-3 to 3.5.

It seems like they have already started to lay the ground work for some things by rolling out the chatgpt mac app that can see your screen while having a conversation with you in relation to exactly what it’s seeing.

Also Ben Newhouse at openAI has said interesting things lately about an “industry defining zero to one product” that takes advantage of the most advanced openai “upcoming models”

And there was recently an openAI job listing as well that mentioned: “In this role, you will build a 0-1 product that brings ChatGPT to where our users are already doing their work - the desktop”

<image>

[–]Formal-Dentist-1680 1 point2 points  (0 children)

Nice, found a job post with the same:  https://openai.com/careers/software-engineer-desktop/

Also, would point to Sam saying the ideal agent interface on the phone is watching it click and type through apps and giving it verbal feedback:

"I could say, 'okay AI assistant like you put in this order on DoorDash please' and I could like watch the app open and see the thing clicking around and I could say, 'hey no not this or like um.' There's something about designing a world that is usable equally well by humans and AIs that I think is an interesting concept. Excited about humanoid robots than sort of robots of like very other shapes, the world is very much designed for humans and I think we should absolutely keep it that way and a shared interface is nice." https://youtu.be/nSM0xd8xHUM?si=hf6USJjKa6AE5AeG (23:05)

When I saw that, I thought he must alluding to desktop because it's very unlike him to precisely, transparently leak anything on a podcast. Then a few days later, they announced the Mac app (but without the GUI interaction, yet). 

Final thought: the interaction paradigm changes are what get people's attention. Ex: Sora and GPT-4o voice mode were both more viral than the GPT-3.5 to 4 upgrade (and the most viral part of GPT-4 was image as an input). I think they understand this because, they totally ignored all the cool stuff GPT-4o can do with images and only focused on voice mode because it felt like a new, exciting interaction paradigm. I think one of the few 0 to 1 interaction paradigms left is GUI interaction so they're saving that to make sure their next big release makes a splash. 

[–]airhorny 5 points6 points  (1 child)

All things considered this is a pretty sensible post. Delete it, it doesn't belong on this sub!

[–]dogesator[S] 6 points7 points  (0 children)

Damn you’re right. 😔

[–]pigeon57434 3 points4 points  (18 children)

I think people put way too much weight in that "draft blog" about GPT-4.5 it was most likely just a testing thing and even if not it still doesn't give much useful evidence to support really anything so I find you mentioning it kinda useless however your other points seems fairly reasonable

[–]dogesator[S] 7 points8 points  (17 children)

Fair point, I appreciate you think the other points are reasonable atleast.

[–]BackgroundHeat9965 1 point2 points  (0 children)

AGI in 2 weeks

[–]Tasty-Ad-3753 1 point2 points  (2 children)

I was at a conference last week where one of the speakers (CEO of Chegg) who is friends with Sam Altman specifically referenced that he has used GPT5 - presumably either a checkpoint or one that has not finished full safety training etc, but unless he got confused about naming conventions it implied to me that if they already basically have GPT5 in the bank then they would not do a 4.5 release

Also they mentioned only recently that training started on their most up to date model, but if people are already using GPT5 that would strongly imply it was whatever comes after GPT5 that is in training

Either way I think it would be weird for them to not release any kind of new frontier model at all soon after making 4o free 🤔

[–]uuuuooooouuuuo 2 points3 points  (0 children)

I reckon they might have trained a GPT-5 scale model but without all the new architectural improvements, so it's completely uneconomical to serve to a global user base

They basically get to see the next order of magnitude 2 years earlier than we do

[–]dogesator[S] 0 points1 point  (0 children)

Often companies may refer to such things as just codenames like “here is the model code named greenfrog that we’re not naming as a specific GPT yet” and it’s just GPT-4.5 but perhaps the chegg CEO just assumes it’s GPT-5.

[–]Hopeful-Cap-8117 0 points1 point  (1 child)

Which gpt should theoritically be agi?

[–]dogesator[S] 0 points1 point  (0 children)

If you mean something that is able to do at-least 50% of todays knowledge work jobs as good as the average person in those jobs, then maybe sometime around GPT-6,7 or 8, probably one of those.

But just because it’s capable enough to do so doesn’t necessarily mean it’ll replace that percentage of jobs. The nature of how humans do work might change completely but might still be called work.

[–]Kingrock123 0 points1 point  (1 child)

As other GPT and LLM vendor compete strongly, 33 months to the next substantial release will be too long. However, the quality of such release will be determined by the most competing model at the time. We also have to look out for false claims about latter models including GPT 5. We may have to evaluate any of the claims before trusting them.

[–]dogesator[S] 0 points1 point  (0 children)

The .5 leaps have always been considered fairly substantial as they have been 10X raw compute jumps. (Full generation leaps have been 100X compute jumps)

Xai and OpenAI both seem to have about the same compute now of 100K H100 clusters just barely finishing being made operational (according to official info and reliable analysts), that’s enough for around 15X raw compute over original GPT-4, so these are essentially the first GPT-4.5 level models that should be releasing around EOY. Exciting.

[–]Latter-Elk-5670 0 points1 point  (1 child)

TrendForce reports that NVIDIA is still on track to launch both the B100 and B200 in the 2H24 as it aims to target CSP customers.

so basically training on the first B200 192GB VRAM cards might be starting now and will take a few months
So truly next gen models can be expected in 2025 from all kinds of AI factories as these are the first GPUS really targeting AI with a doubling of VRAM.

GB200 server rack contains 18 Grace CPUs and 36 Blackwell GPUs. so 36x192= 7'000 GB VRAM (llama 405b download is 820GB) so you can clearly train way bigger models now

The estimates suggest a fully-loaded GB200 NVL72 server with 72 GB200 and 7'000 GB Vram costs $3 million.

[–]dogesator[S] 0 points1 point  (0 children)

“Launching” and ramping up in mass production are a big difference. Nvidia CFO said himself that production won’t ramp up until 2025.

Based on the supply chain info right now it seems there won’t be new large scale clusters with over 100K B200s until Q1 2025 at the earliest. We also have info confirmed from xAI that they are moving as fast as they can but still are not expecting to be able to have a 300K B200 cluster built until summer of 2025 and this seems in-line with what is possible for other companies too.

There is also new info from reputable analysts at semi-analysis showing evidence and satellite imagery of OpenAIs latest cluster planned for around 100K-120K H100s, as of Mid-june it’s shown that this cluster is about 60% finished being built, so it seems OpenAI probably started training on about 50K-66K H100s around May and then plans to continue training on the full cluster when it’s finished around maybe July or August for a couple more months.

Regarding vram for training, I think you’re getting it mixed up with inference. When you’re inferencing a model you usually want the vram footprint as low as possible so you can fit the model into a single node or even single GPU if possible since multi-node inference becomes much less cost efficient and not very paralellizable, especially when doing local inference in low batch sizes. However for large training runs it’s completely different from inference and the amount of vram in a single server rack actually doesn’t change how large of a model you can train, no large training ever uses single server racks, they use hundreds of server racks together with millions of gigabytes of vram that could run a 100 trillion parameter models if you wanted to, so their parameter count in training was never really limited by vram capacity in the first place. The size of the model you train mainly just comes down to how much total compute you have in flops, along with how much flops efficiency are you getting, along with what parameter-token ratio you want to use and how much total training time do you want it to last. Increasing VRAM capacity simply allows the training run to go faster and increases the training efficiency by allowing a bigger batch size during training to better utilize all the potential flops of the GPUs, but it doesn’t inherently practically unlock some new higher level of parameter counts that weren’t possible before since most training VRAM is not even used for parameter count anyways.

By the way, VRAM was already mostly doubled back when the H200 was announced. Right now the biggest clusters being built or nearly finished being built are around 100K H100s such as OpenAIs cluster that was nearly finished as of June and xAI cluster which is similar size and nearly fully operational too. Some of the first H200 clusters are being planned and started right around now as well, Nvidia officially shipped out the first ever fully connected H200 server just about 2 months ago.

[–]Realistic_Stomach848 0 points1 point  (0 children)

They could get the h200 and b100s and decided to retrain it again, incorporating q*. What should be called gpt6, will be released as gpt5