Try o3-pro in ChatGPT for $1

Is AI a bubble?

Jun 24, 2025

Will AI progress slow down? Current frontier AI models cost $100M+ to train, but in the old scaling law pre-training paradigm this was a one-off cost that scaled well i.e. it had a low marginal cost per query. Now this paradigm has now hit diminishing returns: New frontier models trained with ~10x more compute than GPT-4 (like Grok) haven’t wowed enough to justify spending another 10x more—~$1B—on pretraining.

And so now, we’re in a new 'inference scaling paradigm’¹ AI firms scale inference by executing long internal chains of thought —then discard the scratch‑pad and show the user a short answer. This takes a lot of compute. For one, OpenAI just released their latest inference model — o3-pro. While it shows modest gains over the o3 base model on reasoning, math, science and coding benchmarks,² it often takes ~10 mins per query and costs $200 / month.

But I’ve found a promo code (see below) so you can trial o3-pro with ChatGPT Plus Team for just £1/$1/€1, so you can see what all the buzz is about! How’s this possible? For one, it’s a one month trial with a limited number of queries for each of the 5 accounts you can set up.

More crucially, it’s subsidized by VC money to inflate OpenAI’s user number metrics and to prop up their ~$300B valuation.³

Consider the ever faster increase in weekly ChatGPT users:

Feb '23: 100M⁴

Sep '24: 200M⁵ of which 11.5M paid, Enterprise: 1M⁶

Feb '25: 400M⁷ of which 15M paid⁸ / Enterprise: 2M

Mar ‘25: 500M of which 20M paid⁹,¹⁰
May ‘25: ~1B¹¹ / Enterprise: 3M¹²

You can see that they converted 11.5M out of the first 200M users but only got 3.5M users out of the more recent 200M to pay for ChatGPT. Your $1 trial adds another five paying enterprise customers to these numbers. And if you use o3 a lot, you also add to the $15B in (mostly compute) costs OpenAI burns through every year—subsidized by VC money.¹³
Is that realistic? Only ~350M iPhone users from richer countries have downloaded the ChatGPT iOS app¹⁴ and many of the other 650M come from poorer countries, where many use ChatGPT via WhatsApp¹⁵ or even flip phones,¹⁶ and they won’t pay $20/month (e.g. in 2024, user numbers tripled in India, which is now OpenAI's second largest market¹⁷). Some create multiple free accounts to get around rate limits messages and image generation (e.g. turning photos into anime), which props up user numbers further.¹⁸,¹⁹ OpenAI incentivizes this: phone numbers or email addresses are no longer required during sign up²⁰ (ChatGPT search requires no sign up at all now).²¹

Now OpenAI can claim:

they have 1 billion users
are the fastest growing company ever
If they time the subsidized user push right their model of expected annual recurring revenue is $10B/y and $11B in 2025 is possible²²,²³ up from the hard metric of annual revenue of $3.8B in 2024²⁴ They expect $174B in revenue and 3B users by 2030²⁵

While OpenAI uses the standard playbook to boost its valuation (Uber took years to become profitable and FB and Coinbase²⁶ etc.²⁷ inflated user numbers; even GoJo does it in a subplot in Succession), AI stocks could crash.²⁸ Manifold users deem this realistic²⁹ and indeed, the market expects AI to create trillions of value by 2027.³⁰ Meanwhile hundreds of OpenAI's current and ex-employees sold their stock.³¹

To get $10B/y in revenue, you need to:

Sell 1-10*$1-10B/y government contracts: one or a handful of ‘country‑scale’ contracts (e.g., national cloud, health‑care backbone, defense; e.g. like Lockheed). So far OpenAI has only smaller contracts (e.g. a $200M DoD contract).³²

Sell 4M * ~$2.5k/y o3 pro‑seats (High‑value per‑seat licenses to professionals (think design, data, or dev tooling).

Sell 40M * ~$250/y ChatGPT subscriptions - they are far off and want to double prices to $44 a month by 2029.³³

This seems unrealistic. The precedent of the fast growing social media winner-take-all industry had much stronger network effects that 'lock in' users longterm. LLMs will be commoditized like public utilities³⁴ where users, and especially enterprise customers, will switch if a better/cheaper LLM comes out.³⁵ And indeed, because recent AI progress has hit diminishing returns, there are now many frontier models that are of similar quality for most many use cases - many people use LLMs merely as a writing assistant ³⁶ (e.g. Gemini, ChatGPT, Claude, Grok, LLAMA, DeepSeek, etc.) and there’s tough competition driving down profits.

And so, AI could be a bubble, which has implications for forecasting the progress of AI. Given that inference scaling is very costly, it’s even less clear how to break even for models that use 100x more compute that are predicted to emerge by 2027.³⁷

But I digressed, here’s the Promo code (DON’T FORGET TO CANCEL THE TRIAL WITHIN THE TRIAL PERIOD UNDER THIS LINK AFTER YOU SIGN UP IF YOU DON’T WANT TO PAY $30 PER SEAT; tip: if you want to add more seats and you own bob@gmail.com, you also own b.ob@gmail.com, b.o.b@gmail.com, etc.)

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