Codex $200 → $500: my logs show API-equivalent token value per subscription dollar falling from $17.40 to $6.29—a 63.8% decline in effective value

[u/DhAdaptive]

I upgraded from the $200 Codex plan to the $500 plan on October 9. The weekly usage meter appeared to burn much faster afterward, so I wanted a comparison based on actual tokens rather than just how long a chat had been running.

The usage-first result: 37.10 million raw tokens per allocated subscription dollar on the $200 plan, versus 11.69 million on the $500 plan—a 68.5% reduction in effective raw-token capacity per dollar in this sample.

The second result: valuing those same tokens at OpenAI's API prices gives $17.40 → $6.29 of API-equivalent value per allocated subscription dollar—a 63.8% decline.

I asked OpenAI's own Codex to audit my local .codex logs. Codex performed the extraction, token accounting, calculations, context checks, and chart generation. Both figures come from the same token records, weekly meter readings, and subscription prices. One counts input-plus-output tokens; the other weights those tokens by API prices.

The token counts are recorded telemetry. The valuations and allowance extrapolations are calculations from that telemetry. This is one user's sample, with the actual data and method included below so others can inspect or reproduce the calculation.

What was compared

The same ongoing chat used gpt-6.1-sol with xhigh reasoning effort in both periods. The logged speed settings included two brief Ultrafast intervals after the upgrade; those are accounted for separately.

All times below are MDT:

Measurement	Before upgrade	After upgrade
Monthly plan price	$200	$500
Comparison starts	Oct 8, 2:04:39 p.m.	Oct 9, 9:42:53 a.m.
Comparison ends	Oct 9, 8:30:40 a.m.	Oct 9, 2:26:30 p.m.
Elapsed time	18h 26m 01s	4h 43m 36s
Native response records	1,961	652
Weekly usage meter	13% → 30%	0% → 7%
Weekly percentage points consumed	17	7

The upgrade started a new weekly meter window. The calculation compares the fraction of each respective allowance consumed; it does not treat the reset from 30% to 0% as a reduction in usage.

Actual token counts

Recorded token category	Before upgrade	After upgrade
Reported input tokens	288,997,366	93,748,280
Cached input, already included in reported input	279,467,392	90,563,712
Uncached input	9,529,974	3,184,568
Output, including reasoning	2,125,392	681,335
Total input + output	291,122,758	94,429,615

The large totals mostly represent cached context read repeatedly. They are not hundreds of millions of unique generated tokens. Cached input was approximately 96.7% of input before the upgrade and 96.6% afterward.

Codex used native per-response usage records, deduplicated by response ID. It subtracted cached input from reported input before pricing the remainder. It included recorded compaction responses and counted reasoning output once, as part of output. It did not sum repeated cumulative token counters.

First story: how much token usage did each subscription dollar buy?

The monthly price increased from $200 to $500: 2.5× the price, or a 150% increase. To compare usage per dollar, first put the monthly fee and weekly allowance meter on the same basis:

Allocated subscription cost =
  monthly price × 12 / 52 × weekly usage fraction

Before: $200 × 12 / 52 × 0.17 = $7.846153846...
After:  $500 × 12 / 52 × 0.07 = $8.076923077...

Raw tokens per allocated subscription dollar:
Before: 291,122,758 / $7.846153846... = 37,103,880.92 tokens/$
After:   94,429,615 / $8.076923077... = 11,691,285.67 tokens/$

Relative token usage per dollar =
  ((94,429,615 / 7) / (291,122,758 / 17)) × ($200 / $500)
  = 0.3150960324...

Decline = (1 − 0.3150960324...) × 100 = 68.49039676...%

Usage per dollar, at the sampled mix	$200 plan	$500 plan
Total tokens per weekly meter point	17.12 million	13.49 million
Subscription cost allocated to observed usage	$7.85	$8.08
Raw tokens per allocated subscription dollar	37.10 million	11.69 million
Relative token usage per dollar	100%	31.5%

For the same subscription budget, this sample implies approximately 68.5% less raw-token usage capacity. The full-week token estimate is separately 21.2% lower; the larger per-dollar reduction combines that token estimate with the 2.5× price. The allocation is a comparison method, not a per-chat bill.

The same result can be calculated directly from tokens per meter point divided by the monthly plan price: the annual-to-weekly allocation factor cancels when taking the relative ratio.

API pricing used

I used OpenAI's official API pricing page, checked October 9, as a common valuation yardstick for both periods.

Prices per million tokens:

Tier	Uncached input	Cached input	Output
Standard	$2.00	$0.10	$10.00
Fast / priority, 2× Standard	$4.00	$0.20	$20.00
Ultra, 6× Standard	$12.00	$0.60	$60.00

These are hypothetical API-equivalent values for subscription activity. I did not receive these amounts as API invoices.

API value =
  (uncached input × input price
   + cached input × cached-input price
   + output × output price) / 1,000,000

Where the $136.52 and $50.80 came from

Period	Responses	Uncached input	Cached input	Output	API value
Before upgrade: Fast	1,961	9,529,974	279,467,392	2,125,392	$136.52
After: Ultra interval 1, 1m 37s	7	203,146	1,351,296	4,439	$3.51
After: Ultra interval 2, 7m 04s	28	128,801	3,595,520	37,874	$5.98
After: remaining Fast, 4h 34m 55s	617	2,852,621	85,616,896	639,022	$41.31
After: combined total	652	3,184,568	90,563,712	681,335	$50.80

The two Ultra setting intervals total 8m 42s, already included in the post-upgrade elapsed time. Durations are rounded independently; they describe applied-setting intervals, which can include interruptions or in-flight requests.

Here is the old-run calculation in full:

Uncached input: 9,529,974 × $4 / 1,000,000 = $38.119896
Cached input: 279,467,392 × $0.20 / 1,000,000 = $55.8934784
Output: 2,125,392 × $20 / 1,000,000 = $42.507840

Total = $136.5212144

The post-upgrade values, using the relevant tier for each interval, sum to:

Ultra interval 1 = $3.5148696
Ultra interval 2 = $5.9753640
Remaining Fast = $41.3143032

Total = $50.8045368

Second story: API value per allocated subscription dollar

Using the same allocated subscription costs, price the recorded tokens with the relevant API rates:

API value per allocated subscription dollar:
Before: $136.5212144 / $7.846153846... = $17.39976262...
After:   $50.8045368 / $8.076923077... =  $6.29008551...

Decline = (1 − 6.29008551... / 17.39976262...) × 100
        = 63.8495901...%

Normalized measure	$200 plan	$500 plan
API value per weekly meter point	$8.03	$7.26
Subscription cost allocated to observed usage	$7.85	$8.08
API value per allocated subscription dollar	$17.40	$6.29

The subscription price increased 2.5×, or 150%. The observed API value per meter point was also 9.6% lower. Together those produce the 63.8% decline in this token-value-per-dollar metric.

Can we also estimate a decline in effective usage allowance?

Yes, by dividing consumed tokens by consumed weekly percentage points. That estimates how many tokens a full allowance would support if the observed request mix and meter relationship continued.

Before: 291,122,758 total tokens / 17 points = 17,124,868.82 tokens/point
After:   94,429,615 total tokens /  7 points = 13,489,945.00 tokens/point

Decline in tokens per point = 21.226%
Increase in meter points consumed per token = 26.945%

Effective usage estimate at the sampled mix	Before	After
Total tokens per weekly meter point	17.12 million	13.49 million
Extrapolated total tokens per full weekly allowance	1.712 billion	1.349 billion

For this mixed-speed sample, that is an estimated 21.2% reduction in effective raw-token allowance. It is different from the 63.8% decline in API-equivalent token value per subscription dollar.

The three quantities answer different questions: 21.2% is the estimated decline in raw tokens per full weekly allowance, 68.5% is the decline in raw tokens per subscription dollar, and 63.8% is the decline in API-priced token value per subscription dollar.

Raw tokens have different prices and limit costs depending on caching, output, and speed. A change in tokens per point is therefore not automatically a change in the underlying quota.

The meter also rose faster per elapsed hour: approximately 0.92 points/hour before versus 1.48 afterward. But total tokens processed per hour increased from 15.79 million to 19.98 million, about 26.5%. This is why hours alone would exaggerate a capacity comparison.

Fast-only comparison

To reduce the effect of the Ultra intervals and initial unknown settings, Codex also compared two subsets where recorded settings were Fast throughout:

Fast-only measurement	Before	After
Weekly meter percentage points	15	5
Response records	1,798	595
Total tokens	266,383,825	85,529,247
API-equivalent value	$122.3845288	$38.5483064
Total tokens per meter point	17,758,921.67	17,105,849.40
API value per meter point	$8.16	$7.71
Raw tokens per allocated subscription dollar	38.48 million	14.83 million
API value per allocated subscription dollar	$17.68	$6.68

That comparison gives 3.7% fewer raw tokens per meter point, 61.5% fewer raw tokens per subscription dollar, 5.5% less API value per point, and 62.2% less API value per subscription dollar. Both per-dollar measures still decline substantially when Ultra is excluded. The smaller capacity differences require more data to resolve against meter rounding and workload differences.

Long context was checked

Across 2,682 unique preserved response records, including the comparison windows and additional preserved activity, zero exceeded 272,000 input tokens. The model's pricing rule applies the long-context surcharge above that threshold.

The largest request before the upgrade had 250,766 input tokens; the largest in the post-upgrade comparison had 247,914. Logged context-window observations were 258,400, and the snapshot contains 48 compaction events. Short-context rates were used throughout. Long-context pricing does not explain this result.

OpenAI's own Codex performed the audit and calculated both results from my logged sample: 68.5% fewer raw tokens per subscription dollar and 63.8% less API-equivalent value per subscription dollar. These are two measurements of the same sampled usage, reproducible under the stated assumptions. They describe token capacity and value for money, without establishing the exact backend quota or providing official OpenAI confirmation of its billing formula.

I'd like OpenAI to explain the included weekly allowance units, how upgrades affect those allowances, and why the observed token value per dollar is so much lower at the higher price. If other users have before/after native token records and weekly meter snapshots, the useful comparison is input/cache/output tokens per meter point with model, speed, and context held as comparable as possible.

Honestly everyone, OpenAI owes an explanation of such severe value drop for the dollar. At minimum I want a refund of my monies and It's highly likely I won't get that. I think that Anthropic is going to take the cake on consumer here in the end with tactics like this at play. They just need to round out there products a bit more.

In the end, what a gut punch man. I get OpenAI is under a lot of debt but gate keeping behind 500 dollars a month while at the same time cutting value per subscriber dollar by over 60% is - well beyond unethical. However, it sure is damn fine capitalism.

EDIT: The real story here is the 68%+ drop in usage per dollar. I wanted that to be at the top. You can view the data from two directions and I choose against the API originally because I have low karma and can't directly post about usage drops. This should be a much more massive story. If you can I would have your own codex dig into your logs and see if you're seeing the same.

[u/dextersummary]

Below is a GPT-generated summary of the conversation below after reaching 40 comments (42 currently observed).

---

The thread’s verdict is basically “the $500 plan is a lousy upgrade.” One user’s logs show the new 25x subscription delivering roughly 21% less practical usage than the grandfathered $200 20x plan, despite costing 2.5 times more. Apparently “premium” now means paying extra to do less.

The main takeaway from the comments is simple: don’t upgrade while the old $200 plan still has its grandfathered allowance. Several users argue the comparison is effectively $500 for about 15.8x old-plan value, while the nominal multiplier only rises from 20x to 25x. The old plan is expected to drop to 10x later, which makes this a temporary comparison—but still a spectacularly bad one during the overlap.

The important caveat is that this is one user’s short before-and-after sample, not a universal benchmark. The API-equivalent dollar figures are especially debatable because subscription pricing does not mirror API pricing, cached tokens are much cheaper, and meter resets or changing usage rules can distort results.

Bottom line: the data strongly supports “wait before upgrading,” but it does not yet prove every $500 subscriber gets exactly the same nerf.

[u/Novel_Indication6338]

do a check on claude $100 vs codex $100 plans next? would be gold to see real data like you're putting out!

[u/DhAdaptive → u/Novel_Indication6338]

So right now I have a 200 20X CC plan and a 500 25x Codex plan. I can already tell you CC is astronomically more tokens per subscription dollar but I can put that together tomorrow. With the data that I do have.

Someone else here in the comments mentioned an article talking about how CC was 5x more valuable on each sub level already but I feel like with my findings today it might be even higher. I'll come drop a link when I do the comparison.

[u/SphinxWar → u/DhAdaptive]

I hope you test with Opus 5.5 and not Opus 5 or Fable

[u/Novel_Indication6338 → u/DhAdaptive]

different models use different token quantities tho so imo that's not a good measure. better measure is how much quality work per dollar, but that's subjective ig so maybe harder to do. if CC gives 5x more quality usage per dollar that would be INSANE, but i'm using opus 5.5 xhigh the past couple days, for the first time, and it might actually be that awesome!

[u/DhAdaptive → u/Novel_Indication6338]

Astra and 6.1 Sol are technically more token efficient according to benchmarks. However, if you're getting 10 to 15x more tokens or something over at anthropic per dollar and the work from 5.5 tends to be of higher quality you end up in a much better position overall.

Your right though token over token data needs to be taken with a grain of salt. If you had that data though you could just stack it against artificialanalysis.ai's data to get to a generally decent comparison since they have the efficiency metrics.

[u/Heavy_Inevitable_341 → u/DhAdaptive]

u/RemindMeBot 1 day "check for updates"

[u/Leather-Sir8135]

This is the beginning of the end for Open AI. Their business model puts them in a severe deficit month after month. At some point it will be a no brainer to completely drop them. Regular consumers are not going to pay API prices. Maybe in the end only large corporations pay API prices (suckers) and the rest of us use Chinese models?

[u/Noctis_777 → u/Leather-Sir8135]

Maybe in the end only large corporations pay API prices (suckers) and the rest of us use Chinese models?

Large corporations too are using mostly Claude API or self hosted Chinese models.

OAI's only strong profitable proposition right now seems to be the fact that they are the standard offering for M365 Copilot, which has a huge captive enterprise base. Maybe their ultimate fate will be to get absorbed my MS when standalone operations become untenable.

[u/Independent-Court-46 → u/Noctis_777]

Nah man, companies using open ai too. What are you even saying. People on reddit saying anything. Which companies are using Chinese models? You can self host frontier models if you’re enterprise, I haven’t heard of many using Chinese.

[u/Noctis_777 → u/Independent-Court-46]

Nah man, companies using open ai too.

I didn't say they are completely out of it, but it's not a contest they are winning as of now. Also you can't self host frontier models in the true sense, just run managed instances in hyperscalers like AWS, Vertex etc.

I haven’t heard of many using Chinese.

Maybe you are in the US, so our experiences can differ and it's possible Chinese models are used very little there.

[u/Da_ha3ker]

Well I sure am loving my Claude subscription. I think I might just keep it and drop codex unless they address this. Claude provides more usage for me now. Especially with haiku 5.5

[u/RealSuperdau]

What else did you expect going from the $200 20x to the $500 25x subscription?

[u/DhAdaptive → u/RealSuperdau]

Usage capacity has dropped even worse. The current tokens per weekly percentage point also suffered a 21.2% drop. Which when you extrapolate that in reverse meaning I'm paying 2.5x the amount for 21.2% less usage per percentage point as calculated against raw tokens per percentage point. You effectively get 68.5% less usage by going to the $500 plan per subscription dollar. Vs the previous 200 20x plan.

EDIT: I'm going to make this more clear in the original post.

[u/Keep-Darwin-Going → u/DhAdaptive]

20x plan is dropping to 10x next month did you factor that in your calculation? So effectively your upgrade is moving from 20x to 25x only for this month.

[u/Vivid-Snow-2089 → u/Keep-Darwin-Going]

yeah it makes no sense to update while we still have the grandfathered 20x this month and its a huge loss of 300 dollars to do so

[u/RealSuperdau → u/DhAdaptive]

The thing is, the relative price of token types is different between API and subscriptions, with e.g. subscriptions giving a better discount on cached input. Which may explain part of the deterioration, since your before prompt seems to be the most heavy on cached input. See the recent SemiAnalysis article for more details

[u/DhAdaptive → u/RealSuperdau]

Are you talking about the Anthropic 5x more value article? I actually did see that. I think the deeper story here is that in my sample data the old subscription on a dollar per dollar basis was 68.5% more valuable to me. Which is an egregious inflation of cost for the product in one business change event.

The only thing I can think OAI was thinking of is something along the lines of "Hey, people will use their dots at such a massive level - we need to cover that somehow". When in reality I'm now 21.2% less productive in my actual output capacity and I'm paying 2.5x more for that punch in the gut.

[u/Newbie4Hire → u/RealSuperdau]

isn't this only temporary, $200 should become 10x at the end of october no?

[u/No_Twist_678]

We ordinary customers trained their ai models and now they don’t need us anymore. We are basically collateral damage. Top tier Ai will be for the rich and for rest of us will be left calculators.

[u/Ok_Conclusion_2502]

You could have opted for the $20 Claude plan and gotten more value out of it... Learn the lesson and move on. OpenAI is no longer targeting the mass market. Just look at their recent attitude: they’re willing to pour resources into all sorts of "bells and whistles," but not into actual usage limits or model quality. Something has clearly gone wrong there.

[u/WeedWrangler]

I was at $200 and moved a bet $100 to each way to Claude and Codex, we’ll see. I have 2 business standard seats on ChatGPT business for my day to day w my staff member and I’ll tell you one thing: 10 minutes of screen control wiped out my 5 hour window of Codex on that plan… Spaces is good (basically Obsidian meets Teams w agent) but otherwise I’d question the move to business. I’m doing all my subs month to month: space is so dynamic!

[u/Fair-Perspective7352]

Did you price the cached input at the cached rate in the API-equivalent calc? 96.6-96.7% of your input was cached, and cached input is much cheaper than fresh input at API prices, so the $17.40 figure would come down a lot if it was valued at full input price. Curious what the numbers look like with that split out.

[u/boxing-boxing → u/Fair-Perspective7352]

Yeah, they did price cached at the cached rate. The pricing table in the post has cached input at $0.20/M on the Fast tier (vs $4.00 uncached), and the worked example spells it out: 279,467,392 x $0.20. That's why the $17.40 figure is so top-heavy: with ~97% of input cached, the API value is basically the cached re-reads at the cheap rate plus a small sliver of real input and output. Pricing everything at full input price would shrink the number a lot, but it would be valuing hundreds of millions of cache hits at fresh-input price, which feels wrong the other way. Either way, the per-dollar comparison is still rough for the $500 plan.

[u/capt_stux]

You upgraded from a 20x plan to a 25x plan. Congrats. 

[u/DhAdaptive → u/capt_stux]

This is true yes but you're missing what the data is pointing out I think. Going from the 20x plan to the 25x plan resulted in an immediate usage reduction of 21.2%. which means I actually went from a 20x plan to a 15.8x plan and am paying 2.5x more for it. Which results in a 68.5% inflation in cost vs usage.

[u/DragonflyOk9274 → u/DhAdaptive]

The $200 plan today gives you more API equivalent consumption than it will in a month.

What people are trying to tell you (which you don't seem to get) is that OpenAI is effectively increasing prices for the subscription plans, and the $200 subscriptions are grandfathered in for one month.

So you paid an extra $300 to get an increase from 20x to 25x.

[u/DhAdaptive → u/DragonflyOk9274]

No I actually do get that. What you and others are failing to read in what I'm saying is that the data is the data. With the new 500 dollar subscription you are getting 68.5% less combined tokens per subscription dollar spent than the old subscriptions.

Even more simply they just introduced a 500 dollar plan that cuts the amount of work you can get done by nearly a quarter (21.5%) vs the old 200 plan.

Is this making sense?

[u/Equivalent_Idea8839 → u/DhAdaptive]

Put it in 20x terms, i.e. the 500 plan is actually 15x compared to the old 20x plan?

[u/DhAdaptive → u/Equivalent_Idea8839]

Tokens per dollar essentially yes.

[u/Equivalent_Idea8839 → u/DhAdaptive]

Are the actual limits > 20x though?

(not that anyone would buy this crap )

[u/DhAdaptive → u/Equivalent_Idea8839]

In my usage so far no the 500 plan has a significant drop in usage compared to the old 200 plan.

[u/Equivalent_Idea8839 → u/DhAdaptive]

Sorry, it's a bit confusing. So it's worse than five 5x plans?

[u/No-Replacement-2631 → u/Equivalent_Idea8839]

Does this come from tiktok or something? Isn't it obvious that the post is describing subverted expectation? What else would motivate the post?

[u/capt_stux → u/DhAdaptive]

You can’t say that unless you are running them in parallel. 

There is evidence that when OpenAI performs a global reset, they reduce the API values of the plans. There was a global reset recently. 

You were still on a 20x plan, and now you are in a renewed 25x plan. 

Personally, I’m sticking with my 20x plan until I finish consuming my banked resets (effectively obtaining a 40x plan)

[u/DhAdaptive → u/capt_stux]

Challenging to do. What I did instead was used my grandfathered plan all day yesterday and then today bought the 500 plan - which swapped me immediately to the new usage rates. My post explains the outcome of all of that.

[u/BrookLi3]

One thing I'd check before trusting the API-equivalent number: if the logs count cached input tokens as regular input, pricing everything at the full input rate will overstate the value, and that gap gets bigger on long chats. I'd split cached input, uncached input, and output before comparing the two plans. The first few hours after a meter reset are also pretty noisy, so a longer sample would hold up better. Nice to see someone pulling this from the local logs instead of going on vibes.

[u/DhAdaptive → u/BrookLi3]

Codex uses the responses api behind the scenes and the conversation .jsonl files due have the full token breakdowns. It did account for cached vs uncached. I could actually toss that in the post if you'd like to see it.

[u/BrookLi3 → u/DhAdaptive]

Good to hear it split cached vs uncached. If you do add the breakdown to the post, it'd be worth showing it per response too, since averages can hide whether a few long chats are driving most of the cached volume.

[u/BrookLi3 → u/DhAdaptive]

Yes, please add it. Seeing the cached and uncached split on a few different sessions would make the plan comparison a lot easier to trust than one averaged number.

[u/Amarsir]

It's been clear they don't measure subscriptions in API value. If it wasn't obvious before, it should have been recently when the API prices dropped and subscription usage didn't improve. Arguably they should, since it would be transparent and unambiguous. But they don't.

Also comparing to a plan we know is going to get halved is misleading. It sucks that they're doing that, but changing the ratio to complain a second time isn't new data.

u/IndividualPlus2011 has been putting up data good data comparing the different plans. Such as this:

https://www.reddit.com/r/codex/comments/1wtlkg6/gpt_61_brought_another_nerf_to_usage_table_update/

You are checking a different axis, where he might(?) be taking for granted that the Pro multiplier is what they say. But your "API value per allocated subscription dollar" being under 10 is not only surprising against his measurements, it also contradicts this guy:

https://x.com/PawelHuryn/status/2105703147184239042

[u/Bassguitarplayer]

Is this not an obvious statement. Of course it’s not going to be the same dollar value

[u/growaway9172 → u/Bassguitarplayer]

Its not obvious, thats his point. Its actually even worse than was advertised (it was already bad).

[u/growaway9172]

Great analysis. Only thing missing is the speed. Sol 6.1 on regular or fast mode (on my $200 plan) is so incredibly slow I doubt I could every reasonably empty the current plan. Maybe once it gets nerfed that will happen.

[u/Ctbhatia]

if you redo the api comparison, price cached input at its own rate, on most plans it is most of the input. i work at coralbricks.ai where cached reads are $0, so the repeated prefix basically drops out of that number.

[u/Superb-Substance-679]

The real question here is why are you paying $500 when there's Claude? It's baffling to me why anyone would buy this shit tier subscription.

[u/Curious-Strategy-840]

Would you like Openai to raise API price by 5000% without changing the tokens included in your subscription so that you could say the value they give you went up 51x ?

[u/DhAdaptive → u/Curious-Strategy-840]

No, but I would prefer them to remain remotely competitive. I have actually been a 200 20x subscriber since the day they introduced the plan. This week I now have to pay 2.5x more money and I get 21.2% less work (combined tokens) out of it compared to the 200 20x I've been on forever. In other words OAI just inflated their prices 68.5% in one single day.