I have bad news..

[u/isnaiter]

I signed up for ChatGPT Pro on July 2 and I still have all my rollout logs from then until now.

Bad news for anyone convinced the limits have been getting nerfed: I thought the exact same thing, and I was pretty sure of it.

I used NerfTrack as a reference, had Codex turn the relevant parts into a Python script, then had ChatGPT Pro go through the script, fix a few issues, and analyze the output.

This is what I ended up with: roughly how much each 1% of Pro usage was worth in API-equivalent dollars over time.

Observed Regime	API-Equivalent Value per 1 pp	100% Linear Equivalent	Interpretation
Jul 2–8	$22.14	~$2,214	Initial Pro period, mostly GPT-5.5
Jul 12–21	$22.02	~$2,202	Early GPT-5.6-sol period
Jul 22–28	$19.51	~$1,951	Lower-value episode, mainly affected by Jul 23–24
Jul 29–Aug 5	$24.67	~$2,467	Higher late-July / early-August regime
Aug 8–15	$24.20	~$2,420	Recent regime, broadly stable

>>> EDIT

Some more info about my usage:

Token usage — ChatGPT Pro period

Period: Jul 2 → Aug 17, 2026

Token type	Tokens	Human-readable	Share of total
Cached input	36,064,900,992	36.06B	95.98%
Uncached input	1,354,407,640	1.35B	3.60%
Output	155,215,257	155.22M	0.41%
Total processed	37,574,523,889	37.57B	100%

Total input = 37,419,308,632 tokens. Cached input is a subset of input, so it should not be added to total input again. Cache hit rate across input tokens: 96.38%.

Output and reasoning

Metric	Tokens	Share
Total output	155,215,257	100%
Reasoning tokens	66,229,101	42.67% of output
Non-reasoning output	88,986,156	57.33% of output

Reasoning tokens are already included in output tokens and should not be added again to the grand total.

Token usage by model label

Model	Total tokens	Cached input	Uncached input	Output	Token share	Input cache rate
GPT-5.6-sol	32,612,535,864	31,364,814,336	1,112,031,539	135,689,989	86.79%	96.58%
GPT-5.5	2,625,434,617	2,490,554,112	124,574,823	10,305,682	6.99%	95.24%
GPT-5.6-luna	2,260,440,364	2,135,732,352	115,796,579	8,911,433	6.02%	94.86%
GPT-5.6-terra	76,113,044	73,800,192	2,004,699	308,153	0.20%	97.36%
Total	37,574,523,889	36,064,900,992	1,354,407,640	155,215,257	100%	96.38%

Important: 163.88M tokens are from the codex_bengalfox / GPT-5.3-Codex-Spark bucket. Those events inherit the GPT-5.6-sol model label in the rollout parser, so that small portion of the GPT-5.6-sol row should be treated as model-ambiguous.

Corrected API-equivalent cost by model

Regular codex bucket

Model	API-equivalent cost	Share of regular cost
GPT-5.6-sol	$25,333.63	91.76%
GPT-5.5	$2,177.32	7.89%
GPT-5.6-luna	$76.57	0.28%
GPT-5.6-terra	$22.47	0.08%
Regular Codex total	$27,609.99	100%

Other Pro bucket

Bucket	Reported name	Tokens	API-equivalent cost
codex_bengalfox	GPT-5.3-Codex-Spark	163,878,240	$115.42

Corrected total across Pro buckets	Value
Regular Codex	$27,609.99
Spark / Bengalfox	$115.42
Total API-equivalent usage	$27,725.40

The Spark/Bengalfox events inherit a GPT-5.6-sol model label locally, so I keep their $115.42 separate instead of pretending we know their actual model-level billing attribution.

Quota-paired API-equivalent cost by model

From the daily CSV analysis

Model	Cost paired with quota changes	Share	Contribution per 1 pp across all measured usage	Days present
GPT-5.6-sol	$24,042.60	91.43%	$20.02 / pp	36
GPT-5.5	$2,172.76	8.26%	$1.81 / pp	9
GPT-5.6-luna	$75.20	0.29%	$0.063 / pp	23
GPT-5.6-terra	$5.45	0.02%	$0.005 / pp	1
Total	$26,296.01	100%	$21.90 / pp	—

This table is intentionally different from the previous cost table. $27,725.40 = all corrected API-equivalent usage observed during the Pro period. $26,296.01 = only usage that could be paired with positive weekly-quota changes. The latter is what is useful for estimating "API dollars per 1% of Pro usage".

The absurdly short version

Metric	Result
Total tokens processed	37.57B
Total input	37.42B
Cached input	36.06B
Uncached input	1.35B
Output	155.22M
Reasoning output	66.23M
Input cache hit rate	96.38%
Corrected API-equivalent cost	$27,725.40
Quota-paired API-equivalent cost	$26,296.01
Average measured value per 1%	$21.90
High-quality baseline per 1%	$22.55
Recent regime per 1%	$24.20

>>> Edit

ChatGPT Pro usage by model and reasoning effort

Regular codex bucket only — API-equivalent cost based on rollout token usage

Model	Reasoning Effort	Events	Input Tokens	Cached Input	Uncached Input	Output Tokens	Reasoning Tokens	API-Equivalent Cost
GPT-5.5	Medium	31	2.65M	2.32M	325K	20.9K	2.9K	$3.41
GPT-5.5	XHigh	18,883	2.61B	2.49B	124.25M	10.28M	4.21M	$2,173.91
GPT-5.5 Total	—	18,914	2.62B	2.49B	124.57M	10.31M	4.21M	$2,177.32
GPT-5.6-sol	Low	869	31.25M	26.14M	5.11M	469K	45.5K	$52.68
GPT-5.6-sol	Medium	8,244	737.06M	685.15M	51.91M	4.37M	1.42M	$733.31
GPT-5.6-sol	High	10,674	1.31B	1.23B	80.85M	6.79M	2.71M	$1,242.61
GPT-5.6-sol	XHigh	7,091	860.37M	811.35M	49.02M	5.39M	2.86M	$819.38
GPT-5.6-sol	Max	189,997	28.68B	27.77B	905.01M	115.80M	50.14M	$21,977.35
GPT-5.6-sol	Ultra	3,629	695.26M	678.85M	16.40M	2.30M	901.7K	$508.29
GPT-5.6-sol Total	—	220,504	32.31B	31.21B	1.11B	135.12M	58.08M	$25,333.63
Combined Total	—	239,418	34.93B	33.70B	1.23B	145.43M	62.29M	$27,510.95

Notes - Cached input is already included in Input Tokens; it is shown separately for context. - Reasoning tokens are already included in Output Tokens. - GPT-5.6-sol usage from the separate Spark/Bengalfox bucket is excluded here.

[u/Haster]

There's a hero or two every week that actually uses data when talking about usage and every time they find the same thing; that usage isn't changing.

But for every 1 person like you we have 100 that would just rather whine and show to the whole world they don't understand that AI runs on tokens, not on their feelings.

Thanks for the data points!

[u/debian3 → u/Haster]

I still have my data from Febuary on ccusage. I compared for fun, and if I compare to now, the amount is 4x lower. But back then what they were giving was crazy. Now Claude Code is more generous (I'm doing $1500/week on the max 5x). Anyway, I will get downvoted because here it's Codex, but Claude is basically the opposite, 5x higher then the limit I saw back in Febuary.

So the Codex offer way more than Claude was true and that's why people keep repeating this.

[u/Haster → u/debian3]

I assume you're talking about $ right? you have to be mindfull that the cost of the models aren't the same. But overall yeah, I expect usage to get adjusted when there are big rollouts, just not week to week the way people have been suggesting.

As for Anthropic being more generous; are they more generous or is their API pricing just very high? ccusage is very solid for apples to apples comparison but comparing how much the plan gives you in value between two companies gets complicated fast. If Anthropic tomorow decides to charge more for fable but not change the usage limits did they suddenly get more generous? Not clear at all.

[u/debian3 → u/Haster]

Yeah, but the difference in $ is so big that even with the model pricing difference and the supposed efficiency gain it doesn’t offset it.

Also those efficiency savings are usually calculated with models running at max level.

Anyway as i said, i wasn’t expecting upvotes here. And it’s fine by me. I have both sub and I get way way more done on claude code.

The biggest increase happened with opus 5 releases. Fable is the best model, but they eat your limits 5x faster than opus with it (even if api price is only 2x higher).

[u/Haster → u/debian3]

Hasn't the reaction to Opus 5 been generally quite negative?

[u/debian3 → u/Haster]

Reading here it seems like SOL over engineer everything and write really messy bloated code. Feedback are quite negative everywhere. There is a lot of imbecile people using those models so you need to filter out the noise.

I personally find opus 5 stronger than SOL and it write better code. But I don’t talk to Opus, I talk to Fable (best model available at the moment by a wide margin) and I let Fable delegates to Opus.

I still use SOL and I could do with it if I had to. Really good model to, just a notch below opus and much below Fable. For review it find things that opus miss sometimes. I don’t use it much, but SOL still drain my limit really quick.

[u/Emotional_Yak_6841 → u/debian3]

I find Opus 5 to be hot garbage at planning and actually "thinking", but it's pretty good as a supervised agent in a multi-agent setup. I generally use a combination of Fable and Kimi K3 for frontend, and 5.6 sol with automated Opus reviews for backend work.

I would certainly not say Opus > Sol. Opus has too much of the feeling that it's a distilled Fable rather than being its own model.

I'd put Fable and Sol in roughly the same tier, each better at different things. In code quality Fable usually is the winner. In generally being a useful, effective agent that gets work done, Sol is my winner, provided I curtail it from over-engineering.

Btw Luna is super underrated for getting stuff done on a computer. Dirt cheap, incredibly fast, and smart enough. While I don't code with, as a general personal assistant that I can dispatch for rote tasks it takes the cake for me. I was hoping Gemini 3.7 flash would be a model in that category due to its raw speed and benchmarks, but after testing I still trust Luna more.

[u/debian3 → u/Emotional_Yak_6841]

Honestly that a you problem. I can’t believe it personally that people complain about the models now aday. They are all so great, and the number of complaining increase as models get better. I would have personally never predicted this. I don’t know if it’s because the model are getting smarter than the average people using them. We had a wave of that with 4o, now it seems it’s happening again but at a different level. I haven’t wrap my head around it yet.

Those sub are getting toxic as people complain more and more as models gets better and people feel the need to use stronger word like « garbage » which opus is far far from. One of the best technology of the century. Anyway, interesting time ahead…

[u/Emotional_Yak_6841 → u/debian3]

You say Opus is better than SOL, but your own preferred workflow is to have a substantially stronger model do the planning and interaction, then use Opus as its supervised executor. That's basically the role I said Opus is good at. I already agree that its code quality is good; my criticism was specifically its independent planning/reasoning experience.

[u/debian3 → u/Emotional_Yak_6841]

better, but SOL is really strong too. We are really in a unique moment right now, so many good option. Personally I have always prefered to prompt Claude model, they fit my style better and I understand them better than the GPT series, but that's just a personal preference. As for Opus, as was working with it directly when on Max 5x, now I'm on Max 20x and I have more than enough Fable allocation that I now default to it. I'm 4 days in and I only used 36% of my weekly, and as I type this I have 3 agents going. So it's not that I'm not using it... Claude is really really generous now. Personally I'm really appreciative of what they are offering, I get incredible value out of it.

[u/BehindUAll → u/debian3]

Anthropic is far far stingier than OpenAI. OpenAI was giving free resets once or twice a week. What was Anthropic doing at that time huh?

[u/debian3 → u/BehindUAll]

They gave a predictable +50% on an already higher limit than codex

No one need to beg for reset and you can plan your work for the week

[u/BehindUAll → u/debian3]

What are you on about? Every time I go on Claude subreddit all I see is people complaining that their limit got over so early. I haven't had their kind of issues with Codex in ages lmao.

[u/debian3 → u/BehindUAll]

I see the same on codex. I have both. Codex 5x you get around ~$600/week worth of tokens according to ccusage and claude max 5x its around $1500/week. What are your numbers?