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by carbocation 71 days ago
The $20 Plus plan still exists, and does not give access to the pro model.

The $200 Pro plan still exists, and does give access to the pro model.

What is new is a $100 Pro plan that does give access to the pro model, with lower usage limits than the $200 Pro plan.

2 comments

This is still worse than Anthropic's right? Because you get access to their top model even at the $20 price point
It's not worse, Anthropic simply has no equivalent model (if you don't consider Mythos) of GPT 5.4 Pro. Google does though: Gemini 3.1 Deep Think.

GPT 5.4 Pro is extremely slow but thorough, so it's not meant for the usual agentic work, rather for research or solving hard bugs/math problems when you provide it all the context.

I'm genuinely asking, when you say Gemini 3.1 DT is an equivalent model of GPT 5.4 Pro, is there a specific benchmark/comparison you're referring to or is this more anecdotal?

And do you mean to say that you don't really use GPT 5.4 Pro unless it's for a hard bug? Curious which models you use for system design/architecture/planning vs execution of a plan/design.

TIA! I'm still trying to figure out an optimal system for leveraging all of the LLMs available to us as I've just been throwing 100% of my work at Claude Code in recent months but would like to branch out.

Pro and DT model are equivalents because

- internally same architecture of best of N

- not available in the code harness like Codex, only in the UI (gpt has API)

- GPT-5.4 pro is extremely expensive: $30.00 input vs $180.00 output

- both DT and Pro are really good at solving math problems

So, reading the tea leaves, they're either losing subscribers for the $200 plan, or they're not following the same hockey stick path of growth they thought they were... maybe?

Edit: I wonder if this is actually compute-bound as the impetus

Nope, it's just that a lot of people (especially those using Codex) asked us for a medium-sized $100 plan. $20 felt too restrictive and $200 felt like a big jump.

Pricing strategy is always a bit of an art, without a perfect optimum for everyone:

- pay-per-token makes every query feel stressful

- a single plan overcharges light users and annoyingly blocks heavy users

- a zillion plans are confusing / annoying to navigate and change

This change mostly just adds a medium-sized plan for people doing medium-sized amounts of work. People were asking for this, and we're happy to deliver.

(I work at OpenAI.)

Did you modify the Plus plans usage recently or as part of this introduction? Given that Pro plans usage are multiples of it (5x/20x) and given reports of less Plus usage, clarification would be appreciated?

Transparency on this sort of thing is the best way to address negative company sentiment.

I'm honestly not sure, as I don't work on it. My understanding from afar is:

- There was a 2x promotion in March that ended on April 2, so limits have felt tighter since then

- We sometimes reset rate limits after bugs or milestones or because Tibo feels generous, which can make some days feel different than others (they are typically announced here: https://x.com/thsottiaux)

- Recently Plus was tweaked to have a smaller 5h limit but an increased weekly limit

- Lastly, as part of the new Pro launch, the $100 & $200 Pro tiers are getting a 2x promotion, meaning they are temporarily 10x/40x instead of 5x/20x

I've asked our team to clarify the pricing page. Agree it's not clear.

Following up - I was wrong about 10x/40x. Here's how it actually works:

$20 = 1x

$100 = 5X (but temporarily 10x for just Codex til May 31st)

$200 = 20x

We'll send out new tweets and clarify our pricing page.

Thanks for the response. I tried to phrase my postulations as just that, I didn’t intend to be an accusatory.

You like the job? How’s the day-to-day go? Yanking tickets or more organic?

All good, I interpreted it as postulation and not accusation. :)

I do like the job! Much more organic than yanking tickets, though I'm on the model training side of things, rather than product side. Always a balance between short-term sprints patching bad behaviors for the next model vs long-term investments in infra and science that make future work easier. Sometimes the negative press gets to me a bit (it's a very different feeling than 2022 or 2023), but my goal is just to make the most useful product I can for people. It's been wild how much Codex has already changed my day-to-day work, I'm so curious to see what it looks like in 2030 or 2040.

What kind of bad behaviors? How is the whole SDLC lifecycle there? I imagine, given that this tech is kind of redefining how software is being written, it's not your standard workflow pipeline? Are there code reviews at all? Have you been in any particularly interesting meetings about how you're trying to "shape" the models?

I won't misrepresent myself, I've never spent a penny on any of these services. I am just super curious what it's like to work at one of these frontrunner companies. I bet it's pretty neat.

Plenty of people wanted to spend more than $20 but less than $200 for a plan. It's long overdue IMO.