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By uncap they mean, when they first release a model, it’s full precision so it does well on benchmarks. But after few weeks they will start providing a quantized version behind the scenes because it is cheaper to run. Using an older model as an example since 5.6 is still too new. GPT 5.5 would perform worse on the same benchmark months after release.
What do you mean they uncap to generate hype? We pay based on API rates just like most organizations do. There are API rate limits, but we don't run into them. You can clearly see that prior to Opus 5 launching a couple days ago, GPT 5.6 sol offered the best value for the cost by far: https://deepswe.datacurve.ai/ It's a close tie now with Opus 5 out, but for most of July, OpenAI had a huge lead when compared to Fable 5 or Opus 4.8.
I'm guessing you are comparing the free version of ChatGPT to the free version of Claude. That's a bad comparison because ChatGPT's free model is 5.5 instant(downgrading to 5.4 mini after a few questions), whereas Claude gives you Sonnet 5. OpenAI's lead is in their paid models that are available on Plus and higher plans. I've tried both Claude's Fable and OpenAI's GPT 5.6 Sol. GPT 5.6 Sol writes way better code than Fable 5, and costs like 1/4th the cost. GPT is also better at research/search topics and hallucinates less.
GPT is straight up ass. If you've tried both Claude and GPT there is now fucking way you'd be praising GPT.
The efficiency is huge for me. I tried Fable 5, and it got stuck thinking in a loop for like 30 minutes and billed us $25 just to make 0 progress. I've also had a lot of issues with the code Fable writes. GPT 5.6 sol on the other hand gets tasks done in just a few minutes with no issues. And the code is so much better.
Also it’s really efficient, I haven’t seen an increase in our usage compared to GPT5.5 but the results are amazingly great. Was stuck on a bug for 3 weeks and it figured it out and patched it and upgraded the project to the latest version of node in 3 hours
Wait until Claude plugs into Co-pilot just like GPT.
Most companies it’s the only one allowed. And you can plug in GPT. And soon Claude. Why wouldn’t people use it?
Meta needs to do a better job selling their Meta AI app and Meta Muse model. For the casual user (i.e. someone who doesn't want to pay for AI), they have the best product on the market. Period. Meta Muse's ability to identify images, for example, is way better than Chat GPT.
Honestly if they actually develop their own product rather than US OpenAI, hell or just abandon them for Anthropic, then it's the right direction. GPT is hot garbage for consumer use.
Copilot is way better than GPT.
GPT is literally making you retarded. I am watching it in real time, its sad. Humanity cooked if we let probalistic word guessers do our thinking.
Bro, he might not know english but you can't read for real. He explicitely stated he doesn't know english and use GPT to translate and organize the post.
AI companies could do something extremely funny by doing an takeover of NASDAQ by buying NDAQ and then asking Claude, GPT to add a few more hundred dollars to their IPO prices and skip IPO rules
“ Step 3 we see optimization start grab hold where different models are applied based upon problem complexity” They have been doing that since GPT 5.
Tuesday night Chat GPT mental health check in 😎
Once the Chinese release an open-weight model that outperforms GPT, it's fucking over. OpenAI will be a hollow shell at that point. They might as well start selling their compute like Meta, so that we can use it to run Chinese models lmao. Scam Altman can get fucked and so can Dario.
I don't know where a company that doesn't innovate for years go from here. Would I bet on google or apple for where they will be 20 years from now? I think everyone knows the answer. Google is at the edge of innovation and scientific research, they purchased ai research lab "deepmind" for 500 million or so in 2014, not long after, they created AlphaGo which is the precursor of openAI and all the LLMs we saw in late 2020. * 2017: Google researchers published the "Attention Is All You Need" paper, creating the transformer neural network that powers all modern LLMs. * 2018–2019: OpenAI released GPT-1 and GPT-2, establishing the pre-training paradigm. * 2020: OpenAI launched GPT-3 (175 billion parameters), which made LLMs powerful enough for general commercial and conversational use. * 2022: OpenAI released ChatGPT in November 2022, bringing LLMs to the mainstream public.
> That’s not my experience with GPT-5.6 or Claude Opus 5 agreed. my experience with opus 5 has been awesome. it's such a massive help for troubleshooting problems.
That’s not my experience with GPT-5.6 or Claude Opus 5
It doesn't take an expert in financing to realize the only reason they sell every chip they produce is because they keep giving money for companies to buy them. And there's no making that money back either, even if every adult in the USA bought a ChatGPT plus subscription it would only bring in $62B a year, it would take 4 years to pay off yesterday's $250B backstop deal from Nvidia, another 11 years for the $665 of off balance sheet commitments and another 23 years for Altman's $1.4T commitment. And that's just revenue, halve it for costs and you're looking at like 45 years before breakeven lol. I don't expect much revenue to come from businesses either, considering they can't even pay their Actual Intelligences a living wage, and they're all switching over to Chinese models for coding which are much cheaper, can be self hosted and run privately, and can't be shut down by the government at a moment's notice. Kinda important when you build a business around these models Paying that money back looks even more impossible when you consider how fast and efficient local LLMs are becoming. Now I can run local Chinese models on my 7 year old 2080 Super that rival GPT-4o, and it's only going to get better, faster, smarter, and smaller. Why do you think google is force downloading 4gb AI models on google pixel phones and chrome browsers? AI is becoming efficient enough to do stuff on-device now. No need to run inference in the cloud for millions of users when you can just run it on their own device. I really hope everyone makes money, I really do, but fundamentally I can not buy into this market. There's no reason to borrow the cost of five Apollo programs to spend on slop machines.
jfc. no, it’s you who’s dropping links to papers and larping 1. semantic recall and reasoning aren’t the same thing when talking about LLMs 2. this paper is specifically talking about *degradation over different context lengths* and even goes so far as to say the model they used had perfect recall in a certain range. 3. This paper was using GPT 4.1 which *predates reasoning as a fucking concept* and does not reason at all during inference. (See my first point)
Just wanna chime in that I work for the government (Intelligence community) and everyone on my shop defaults to Claude over GPT
After my day of testing some of the LLM's, if any are going to take over and enslave the human race its going to be Chat GPT. That shit was sinister; REALLY! So yeah, invest in Chat GPT. Might as well make money off the annihilator ..before it annihilates us.
Not quite. Kimi K3 is still around %10 cheaper than GPT 5.6, although its cost advantage vastly shrank.
NVDA funding guarantee Chat GPT data center in OH for $500B. What cld go wrong?
They had very good ideas at the right time, released incredible products and services over the past 30 years, but other than AI can you even name the last time there was a “must have” app or device launched by any of them? By my memory, the last time anyone even talked about “you gotta get this app/hardware device” was GPT, and before that it was TikTok. Since GPT launched almost five years ago? Not one app that everyone is talking about or “has to have”. Not one new iPhone that was meaningfully any different from the five iPhones before it. We are reaching the peak of consumer tech the same way we eventually did with the railroads, cars, telephones, etc. Our phones do pretty much everything we need them to, our TVs have every possible feature imaginable, every app that can do anything we need it to has been developed and launched at some point in the past 20 years, we’re like…done. The two last frontiers for all of them are the only two sectors they’ve been dumping the most money into: AR glasses, and AI. Zuck didn’t shove $100 billion up his own ass for Reality Labs to make the Metaverse. That was basically 2% of the entire program, with the rest going toward the Project Orion AR glasses, which SUCK. They cost $10,000, only work in limited lighting conditions, have a four-hour battery life, and make you look like someone who is actually begging to get their ass kicked. So there goes that $100B for the “next great computing platform”, and when you add in the AI spend, it’s clear their only paths away from relative obscurity in the future are AI or AR, and that’s it. Otherwise, they’re glorified billboard companies. They provide a visible platform where companies can host ads and…that’s about it.
Efficiency gains has been priced in. GPT-3 was horribly inefficient and every generation has seen improvements. This is not new information
D. Buy something else (and perhaps keep an eye on QCOM) I avoid 20% in any given industry, and *all* of these stocks are highly dependent on the LLM/data center narrative. That falls apart (and we're seeing stories casting doubt on ROI for it everyone from megascalers to end users weekly), and all of these have a long way down to pre-GPT 3 lows. I wouldn't even touch an index fund now. They're at historic levels of concentration, and close to 60% of market cap is tied to the LLM/data center narrative. I look to companies at reasonable valuations, revenues growing at a pace at least matching inflation, which return cash flows to investors, in current price uptrends. In OPs graphic, only QCOM is attractive to me on valuations, revenue growth, and return of cash flows to investors, but the stock price has yet to find support. I'd consider if it rose above 20 and 50d SMAs. Let others catch knives.
Problem with that thinking is the same with the nuclear arms race,and make no mistake AI is the new atom bomb, the US and western allies will never let the commies in China lead the world in AI or quantum computing. If there’s a military advantage to AI, the US government will do all it can to be in the lead for national security reasons, and the MAD doctrine doesn’t apply if the US is the only one with true general AI not just chat GPT but real multifunctional networked decision making AI. It’s too dangerous and the US will never trust Russia or China to not develop these things behind closed doors and therefore AI is coming so you got two choices, fight the system and get run over, or make the best of it and find a way to benefit from it.