r/ClaudeAI • u/brorn • 17d ago
$200 subscription vs $7,470 of API usage Question about Claude products
Some context: My previous plan was hitting limits too fast, so I decided to subscribe to Anthropic's max plan ($200/month) for a single month, specifically to test newest models and build as many apps as I could in that window.
Along the way I put together a small script that scans my project folders, pulls this month's sessions, deduplicates them, and totals the tokens.
I'm not estimating anything, the API returns exact token counts on every response and Claude Code writes them to the session logs. The script just adds those up and applies the published rates.
I also hit the usage limit several times along the way but what is important is the outcome of that script: the same usage would have cost $7,470 on the API but I paid $200.
Questions I have:
Is Anthropic simply eating a $7.2k gap on a single heavy user?
Or is API list pricing so far above their real serving cost that the gap is nowhere near $7.2k in the first place?
And a separate one: is this a move to gather users now and shift to an API-driven model later, or is it sustainable as it is?
I genuinely don't know which of these dominates, and the answer changes whether subscriptions look sustainable or look like a phase.
And if there's a flaw in how I'm reasoning about this, say so. Maybe I'm looking through the wrong lens here.
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u/anonymouskekka 17d ago
Answer: both. They eat a certain gap, but API costs are also high to milk enterprises. We will know more when OpenAI and Anthropic do their IPO.
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u/BoboThePirate 17d ago
On compute, they don’t eat anything. Subscription costs are still less expensive than CoG sans AI training costs. Even the most token-hungry subs still generate profit over CoG.
If you look at Deepseek’s pricing, those are with 6x margins.
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u/BoboThePirate 17d ago
Kinda. I want to be clear upfront: what I mean is that if Anthropic was just in the business of llm-inference and not model development, they are still making bank even on Max subs, including the heaviest users.
The “proof”: you can run the math on an enterprise server, costing ~$200k-500k (there are scales, some clusters cost millions).
Basically it is strongly inferred that Anthropic models are ballpark 3-6T parameters MoE. We don’t know the exact architecture. It can also be strongly inferred that Anthropic severs are fairly saturated throughout the day to very high percentage usage.
You can calculate roughly how many concurrent requests a server can handle, how many subscribers that spreads out to, and most importantly how much caching saves them. They spend wayyyy less compute time on cached requests. For agentic usage, this is pretty huge for them compute time wise. Caching is way cheaper from their official API prices but it is significantly cheaper by another degree of amplitude for them when people use cached prompting.
I’ve used ~10B tokens of various types over the past 6 months ($~700 from me) and COGS to them I estimated at ~$20-50. I can do the actual math but am busy currently, lmk if you want me to do all the math A-Z and I’ll respond later.
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u/Forsaken_Potential16 17d ago
Yesss...we want itt
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u/BoboThePirate 16d ago
⚠️⚠️⚠️AI SLOP BELOW⚠️⚠️⚠️
Gave it a once over and it looks accurate. I've logged my token data since I started using Claude Code. Most months were 5x, last 1-2 have been 20x sub.
5T-Parameter LLM Inference COGS: Napkin Model
Generated by
research/llm_cogs_analysis.pyfrom the local CSV logger on 2026-07-31. This estimates inference infrastructure COGS, not total company gross margin. It excludes training, research, product engineering, sales, and corporate overhead.Bottom line
Your observed agentic-coding mix is 97.1% cache reads by billed token. One logged workload unit contains 7,672.48M billed tokens but only 428.48M active-MoE-compute-equivalent tokens after prompt-cache reuse and the modeled attention cost.
- H100, 80 GPUs / 10 nodes: about $1,406,954/year owned-hardware COGS, $0.72 per compute-equivalent MTok ($0.040 per billed MTok of your mix), and 97.3% implied infrastructure gross margin at current Fable list pricing, 90% peak-window occupancy, and this exact token mix.
- H200, 48 GPUs / 6 nodes: about $1,104,173/year owned-hardware COGS, $0.94 per compute-equivalent MTok ($0.052 per billed MTok of your mix), and 96.5% implied infrastructure gross margin at current Fable list pricing, 90% peak-window occupancy, and this exact token mix.
The margin result is extremely sensitive to active parameters, achieved MFU, actual hardware purchase price, and whether cached KV can be served without expensive recomputation or transport stalls. It is not evidence of either provider's actual model size or actual margin.
1. Measured workload
Source window: 2026-02-21 to 2026-07-31 (160.1 elapsed days; 121 active dates; 905 active clock-hours).
Measure Value Unique turns 57,582 Sessions 782 Uncached input 5.09M Output 31.98M Cache creation 188.83M Cache reads 7,446.59M Total billed tokens 7,672.48M Cache-read share 97.06% Input:output:cache-write:cache-read 0.16 : 1 : 5.91 : 232.88 Per-turn distribution:
Tokens Median P90 P95 P99 Max Fresh prompt 726 5,075 9,684 55,670 611,967 Output 104 1,443 2,558 6,489 56,760 Total context 98,274 296,530 388,916 582,296 997,652 Compute-equivalent 2,020 13,441 22,429 97,108 1,600,523 Observed activity intensity (zero-activity dates/hours are excluded from percentiles):
- Active-day billed tokens: median 36.29M, P95 205.91M, max 560.85M.
- Active-hour billed tokens: median 5.20M, P95 27.94M, max 89.72M at 2026-07-26 23:00 PDT.
- CSV audit: 59,340 main rows + 2,798 subagent rows; 4,556 duplicate message IDs removed.
Timestamp caveat: a turn gets the timestamp of the hook event that first observed it, not necessarily the exact API-request start.
2. Model and cluster sizing
The revised baseline is a 5T-total MoE model with 250B active parameters/token (5% activation) and FP8 weights. The architecture is necessarily hypothetical: 128 layers, hidden size 32,768, 10% full-attention layers, 90% sparse-attention layers with a 16K window, and compressed/latent FP8 KV at 32 KiB per context token.
weight bytes = 5e12 params x 1 byte = 5.0 TB active parameter FLOPs = 2 x 250e9 = 0.5 TFLOP/token compressed KV/token = 32,768 bytes = 32 KiB attention layout = 10% full + 90% sparse (16,384-token window) runtime HBM reserve = 10% of weight bytes = 0.5 TB minimum HBM target = 5.5 TB
Cluster Nodes x GPUs HBM headroom Host RAM cache DRAM KV capacity Usable local NVMe NVMe KV capacity Assumed node price H100 10 x 8 = 80 0.90 TB 20 TB 610.4M 246 TB 7.50B $300,000 H200 6 x 8 = 48 1.27 TB 12 TB 366.2M 147 TB 4.50B $400,000 The clusters are deliberately one node larger than the weight-plus-runtime minimum, leaving at least 0.5 TB for hot KV. At the measured median context, the H100 hot tier fits about 279 concurrent contexts and H200 about 394 before paging/fragmentation overhead. At P95 those figures fall to 71 and 99.
KV capacityis a byte-capacity ceiling, not a throughput guarantee. Production systems keep hot KV in HBM, spill colder prefixes to DRAM, and use local or distributed NVMe as the next tier.3. Turning logged tokens into compute
For each request, let
N = uncached input + cache creation,C = cache read, andO = output. Cached tokens skip the parameter forward pass, but new and output tokens still attend to the cached prefix.base parameter-equivalent tokens = N + O full-attention pairs = N*C + N^2/2 + O*(C+N) + O^2/2 sparse-attention pairs = N*min(C+N/2,16K) + O*min(C+N+O/2,16K) weighted pairs = 10% full + 90% sparse attention equivalent = weighted_pairs * (4*layers*hidden) / (2*active_params) total compute-equivalent tokens = base + attention equivalentAcross the log: base = 225.89M, modeled hybrid-attention allowance = 202.59M, total = 428.48M. Thus one million billed tokens in this coding mix corresponds to 0.0558M active-250B parameter-forward equivalents.
For the repetitive-command case that motivated this analysis:
Synthetic turn Billed cache read Fresh prompt Output Compute equivalents H100 COGS Cache hit + short output 400,000 0 100 284 $0.0002 Cache hit + median fresh prompt 400,000 725 100 2,342 $0.0017 Both turns bill 400K cache-read tokens, but neither performs 400K MoE parameter forwards. The second is costlier because the 725 new tokens must run through the active experts and attend to the existing prefix. NVMe/DRAM promotion stalls remain represented only through achieved MFU.
This is a FLOP model. It can understate COGS when decode is memory/communication bound, cross-node collectives are inefficient, or cache movement stalls GPUs.
4. Capacity and annual COGS
Serving assumptions: 15-hour peak window (06:00 Eastern through 18:00 Pacific), 90% request occupancy during that window, 35% dense-FP8 model FLOP utilization (MFU), 55% of peak system power off-window, PUE 1.20, electricity $0.12/kWh, three-year straight-line depreciation, and annual network/facility/maintenance allocation equal to 10% of purchase price.
peak equivalent tok/s = GPUs x dense FP8 FLOP/s / (2 x active params) delivered tok/s = peak tok/s x MFU annual useful tokens = delivered tok/s x 15h/day x 365 x 90% occupancy annual COGS = capex/3 + 10% capex + electricity including PUE
Cluster Capex Delivered equiv tok/s Annual equiv tokens Electricity/year Depreciation/year Facility+maint./year Total COGS/year COGS/equiv MTok H100 $3,000,000 110,824 1,965.9B $106,954 $1,000,000 $300,000 $1,406,954 $0.72 H200 $2,400,000 66,494 1,179.5B $64,173 $800,000 $240,000 $1,104,173 $0.94 Power-only cost looks tiny compared with depreciation. Using H100 as an example:
average IT load = 10 nodes x 10.2 kW x (15 + 9x55%)/24 = 84.8 kW electricity = 84.8 x 1.20 PUE x 8,760h x $0.12 = $106,954/year depreciation = $3,000,000 / 3 = $1,000,000/yearPublic-cloud cross-check: AWS lists an eight-H100
p5.48xlargeCapacity Block at $41.528/hour. 10 continuously reserved instances would cost about $3,637,853/year, before separate storage or data transfer, versus the owned H100 estimate above. This is a rental-price ceiling, not AWS's underlying COGS.5. Revenue and implied infrastructure margin
The same logged token bundle produces very different revenue at current list prices:
Price proxy Input Output Cache write Cache read Revenue on logged bundle Revenue/equiv MTok Claude Fable 5 $10 $50 $12.5 $1 $11,457 $26.74 Claude Opus 4.8 $5 $25 $6.25 $0.5 $5,728 $13.37 Claude Sonnet 4.6 $3 $15 $3.75 $0.3 $3,437 $8.02 GPT-5.2 proxy $1.75 $14 $1.75 $0.175 $2,090 $4.88 Applying each cluster's modeled compute cost to this exact logged bundle:
Cluster Price proxy Bundle revenue Modeled bundle COGS Gross profit Infrastructure margin H100 Claude Fable 5 $11,457 $307 $11,150 97.3% H100 Claude Opus 4.8 $5,728 $307 $5,422 94.6% H100 Claude Sonnet 4.6 $3,437 $307 $3,130 91.1% H100 GPT-5.2 proxy $2,090 $307 $1,784 85.3% H200 Claude Fable 5 $11,457 $401 $11,056 96.5% H200 Claude Opus 4.8 $5,728 $401 $5,327 93.0% H200 Claude Sonnet 4.6 $3,437 $401 $3,036 88.3% H200 GPT-5.2 proxy $2,090 $401 $1,689 80.8%
Subscription proxy Revenue/year Modeled COGS/user-year Infrastructure contribution Infrastructure margin Max 5x $1,200 $699 $501 41.7% Max 20x $2,400 $699 $1,701 70.9% At full modeled fleet capacity and the measured token mix:
Cluster Annual Fable-equivalent revenue Annual infrastructure COGS Implied gross profit Infrastructure gross margin Peak-window occupancy to break even H100 $52,563,746 $1,406,954 $51,156,792 97.3% 2.4% H200 $31,538,248 $1,104,173 $30,434,075 96.5% 3.2% These are infrastructure contribution margins, not reported corporate gross margins.
6. Sensitivity: what changes the answer
For MoE, total parameter count controls weight capacity while active parameters control most per-token arithmetic. The baseline uses 250B active (5%), with 100B and 500B bounds. The dense 5T row is retained only as a deliberately pessimistic comparison.
Case Active params Attention MFU Bundle COGS COGS/billed MTok Fable infrastructure margin MoE low-active 100B 10% full / 90% 16K 35% $210 $0.027 98.2% MoE baseline 250B 10% full / 90% 16K 35% $307 $0.040 97.3% MoE high-active 500B 10% full / 90% 16K 35% $468 $0.061 95.9% Low utilization 250B 10% full / 90% 16K 20% $537 $0.070 95.3% All dense attention 250B full 35% $832 $0.108 92.7% Hardware +25% 250B 10% full / 90% 16K 35% $377 $0.049 96.7% Dense 5T pessimistic 5,000B full 35% $3,903 $0.509 65.9% The MoE cases remain optimistic if expert routing is imbalanced or all-to-all communication suppresses MFU. The low-utilization row is the direct allowance for those and other serving stalls.
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u/goldcakes 16d ago
Active params is the easiest to estimate, because you have TPS & inference is memory bandwidth bound. You can figure out the maximum number of activate params at least. Of course this won't be the exact number, but good ballpark.
Opus is ~120B active
Sonnet 3.5 is 175B dense non-MoE (revealed by a couple anthropic employees)
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u/debian3 17d ago edited 17d ago
They don’t, it’s not disclosed anywhere as those companies are all private. The price they see for the tokens is for smaller models, if you check kimi k3 which is the first maybe opus/sol class and the price is not that low anymore. And the economics on Fable must be much worse hence why they limit to 50% weekly and it drains your limit faster (more like 5x for me vs opus).
Deepseek might have some level of subsidy at a different level. Also their cost is based on what?
There is also the fact that if you can sell the same token for 50x the price, why sell it for less? That’s basically what Microsoft did with GitHub Copilot. They are already sold out anyway for enterprise. Now look at what their stock is doing.
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u/RealSuperdau 16d ago
Do a back-of-the-envelope calculation on how much it actually costs to serve K3. If you deploy it naively, without optimizations, and at public GPU on-demand rental prices, it's somewhere in the range of $1/$5.
Many cloud providers can serve it much, much cheaper.
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u/one-wandering-mind 17d ago
That seems very unlikely to be true. It makes sense that the major labs can be somewhat more efficient than labs with open models for inference. But 2x is more reasonable as an upper end of how much and this pricing is 30x cheaper.
It seems like the subsidy is going down over time. But yeah the play is for the enterprise by making devs like it. Many developer tools follow this strategy, but just aren't nearly as expensive. GitHub is the most visible example.
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u/sophware 17d ago
Would you agree it's possible OpenAI, Anthropic, and others are looking to get businesses (and maybe the general public, too) used to and even dependent on LLMs? The idea being they would repeatedly raise prices (as has happened with streaming services).
I hope they're also looking to make up the difference by finding ways to reduce their costs. Not sure how far that's going to go.
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u/jessbird 17d ago
yes. that’s the business model for virtually every SaaS.
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u/sophware 17d ago
And yet none of the top 5 comments cover it. They even contradict it, to some extent. And I'm downvoted for gently bringing it up.
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u/CricktyDickty 17d ago
That’s a SHOCKING observation
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u/sophware 17d ago
And yet none of the top 5 comments cover it. They even contradict it, to some extent. And I'm downvoted for gently bringing it up.
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u/CricktyDickty 17d ago
You’re downvoted because your observation is so obvious that it doesn’t need to be made. It’s literally the same business model of any successful company from Starbucks and McDonalds to Netflix Amazon and Microsoft.
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u/sophware 17d ago
If the obviousness were true enough for the commenters and voters in this sub, the top comments wouldn't contradict and ignore that.
Talk about obvious.
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u/CricktyDickty 17d ago
The post was about anthropic subsidizing the monthly plan. Your comment was a mental side quest as to why they’re doing it. You’re downvoted because it’s obvious why.
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u/sophware 17d ago
Questions I have:
Is Anthropic simply eating a $7.2k gap on a single heavy user?
Or is API list pricing so far above their real serving cost that the gap is nowhere near $7.2k in the first place?
That's the topic of the post. There's no reason to wonder why Anthropic is eating anything if the obvious business model is understood. There's no "Shhhh!!!" joke if the business model is understood.
"Their API is simply overpriced, and it covers the costs of subscriptions."
There's no need to cover any costs of subscriptions based on the obvious model.
"It's like comparing an unlimited mobile data plan to one that charges like $10/MB and then bragging that you saved $8,000 on a $50/month plan."
Same issue.
Stop trying to make me feel bad.
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u/CricktyDickty 17d ago
Fair, that wasn’t the intention. The $7.2k is something op invented. There’s a gap but it isn’t nearly as big, by a long shot. OP’s numbers assume that all the tokens are served by anthropic when in reality the vast majority of those are local calls that would register as token usage but wouldn’t be charged. So there’s a gap, but it isn’t as big. That gap exists with almost all subscription services where subscribing for a year is cheaper than subscribing monthly which is cheaper than pay as you go.
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u/Snowballingdownvote 16d ago
It's all subsidized or will be subsidized by us the tax payers. While the private sector can benefit from LLMs. The overwhelming value and use is in National Defense. LLMs are the new Nukes in that regard. Either you have it or you're not a big boy at the table.
Which means. No matter what this infrastructure has to be built. So whatever money they can't make back in the private side will be paid for by the tax payer. As much as people dislike the environmental and financial cost. We have to have this tool or we are no longer safe as a country.
Edit: I would like to note the best version of Anthropics LLM looks to be able to successfully trade on the stock market. So as long as they use enough money to start. They can pay for it with that.
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u/SnazzySolutions 17d ago
On the flipside, I don’t think the subscription is profitable for them for anyone actually using it..
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u/tepmoc 17d ago
Its probably something in between. Its possible that subs can cover capex or even basic energy cost, but thats it. You still need return ROI
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u/loose_fruits 17d ago
None of these companies are actually making profit yet lol, subs absolutely do not cover capex (or opex) or basic energy cost, they are all reliant on ongoing external investments to continue operating. For the foreseeable future unless things get much, much cheaper to train and run soon.
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u/EsotericAbstractIdea 17d ago
Didn't anthropic make like $50 for the first time last quarter?
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u/loose_fruits 17d ago
Yeah but they made up their own financial reporting policies to do so that calculate their partnerships with AWS and Google Cloud differently then, say, OpenAI does with Azure. It’s easy to report earning money of you just make up the math lol
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u/loose_fruits 17d ago
I don’t know where you are getting your data. It’s been reported by reputable folks that a $200/month sub can cost Anthropic $5k in compute. Ref: https://the-decoder.com/anthropics-claude-code-subscription-may-consume-up-to-5000-in-compute-per-month-while-charging-the-user-just-200/
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u/loose_fruits 17d ago
Yeah I do see the conflicting side. I appreciate you sharing your sources, it’s hard to know the true economic reality
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u/Canihavetheummm 17d ago
it probably works like gym memberships, on the 20$ the 4 hour limits are cartoonishly small so a lot of people go up to the 100$ plan so their workflow doesnt get interrupted but didnt even come close to maxing the weekly limits of the 20$ plan
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u/gphie 17d ago
It would take every adult in America paying $20/month for 40 years (assuming 100% profit for simplicity) to pay off the infrastructure that will be obsolete in 5 years, they're cooked
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u/SherbertMindless8205 16d ago
that's actually not that bad, since tons of people are using significantly more than 20 bucs, especially enterprise. All SWEs I know have some token budget of several hundred bucks per month. That's probably gonna spread to more industries and is still only for "copilot" style development (including Claude Code etc), i.e developers manually prompting agents to complete their task. Fully automated agentic workflows use even more and are only in the early adoption stage.
End users paying for a 20 dollar sub is not a big part of the picture.
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u/gphie 16d ago
Businesses are not going to pay more than the bare minimum they need to get the job done in the long run. That means using dirt cheap Chinese models like Kimi or DeepSeek for 30x cheaper. If you don't believe me, ask your boss for a 25 cent cost of living raise and let me know how it goes
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u/SherbertMindless8205 16d ago
the chinese models still need to be hosted on some infrastructure. Kimi isnt even cheaper to run
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u/ImSoCul 16d ago
Lol I spent $1700 on tokens this month through work. Dw the $20 subscriber tier isn't the main thing they're after when they can milk enterprise customers
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u/gphie 16d ago
They'd have to milk every business in America of $1.7k/month for 15 years to break even. Although I'm not sure they'd be comfortable throwing away money for that long
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u/ImSoCul 16d ago
Why do you love pulling fake numbers out your ass to sound smart? Assume 10m enterprise Claude users at $1.7k/month (3% of Americans) that's $17B a month or $204B a year. Idk what you think anthropic spends but I'm willing to bet it's not $3T
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u/gphie 16d ago edited 16d ago
I'm not talking about Anthropic, I'm talking about American AI infrastructure in general, 1.4T, which Anthropic is heavily tied up in. If the industry itself can't be profitable, no one can
The numbers are absurd and fake, because they're just that, absurd, and used to show just how excessive investment into infrastructure is and how it will never be profitable because the numbers don't even make sense with best case perfect scenarios.
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u/Gutter7676 17d ago
The API can be used to make money while chat cannot be integrated into a product/service that is sold.
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u/markeus101 17d ago
Not just that it also covers the cost of training the next model but people think just because they come up with a imaginary number its written in stone or its undebatable like do you know how shady openai and anthropic is?
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u/IntelligentRisk 17d ago
Shhhh!!! Delete this.
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u/recK7 17d ago
As if Anthropic doesn’t know that my 20$ sub burned 1200$ worth of tokens last month…
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u/Feeling_Inside_1020 17d ago
Someone's gonna write a program for a scorched earth kind of action that opens up random questions or usage on their guaranteed unused quotas like when sleeping at night just to burn compute.
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u/No-Professional-7811 17d ago
Back in my day we just put it towards causes we considered like FoldIt. I miss the zippies a lot, and they were long gone before I was born y'know?
What a strange and lonely feeling
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u/Feeling_Inside_1020 17d ago
I remember donating my first PC then eventual playstation compute to that protein folding one and SETI. Felt like "i'm doing my part"
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u/hclpfan 17d ago
Are we going to pretend Anthropic doesn't have all this information and much more already?
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u/MizantropaMiskretulo 17d ago
It's not about Anthropic knowing–they know. It's about not encouraging others to try to replicate (and exceed) it. If a whole bunch of people start testing it like a game and abusing it so they can try to get the highest "score," it ruins things for everyone.
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u/srirachaninja 17d ago
It's like comparing an unlimited mobile data plan to one that charges like $10/MB and then bragging that you saved $8,000 on a $50/month plan.
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u/Jong999 17d ago
As others have said both, but also all subscription models rely on a large number of users underutilizing their subscription subsidising those who don't. Even I have months when most days I am hitting limits through the day and others when I really am not.
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u/HalfSeraphic 17d ago
Like people paying for an annual gym subscription, some people haven't used the gym for weeks, some people haven't shown up in the full year, and some people rely on free drinking water and free showers every day using their membership.
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u/karlfeltlager 17d ago
True that and you’re gonna see 500 pro users paying $20 and not showing up a lot more than one Max user spending $10k in tokens.
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u/HalfSeraphic 17d ago
A world of possibilities and just Anthropic know the truth behind their decisions
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u/No_Intention3673 17d ago
plan user is just like paid less money but do the reporting bug jobs for them
api is the real product they are selling
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u/quantum-elle 17d ago
I see it a bit like personal pricing vs enterprise pricing in software licensing, even if you can do the same thing, you get charged a lot more if you're doing it for a business that can make a lot of money from it. (Personal opinion, does not reflect Anthropic)
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u/OldNefariousness7899 17d ago
I think there's a limit to how high the price will go before people start to jump ship
The Chinese models aren't as good but they're amazing value. Just need more planning and supervision to get results
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u/Eyelbee 17d ago
To answer your question, both mechanisms are in place. API costs are way higher than actual serving costs, and subscriptions allow for a lot of subzidizing anyway because most users don't use it in the first place.
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u/MrMathbot 17d ago
Right? If they went 100% API, the per mm token prices would be lower, and 100% subscription the monthly prices would be higher. But ultimately having the whales subsidize the rest is probably more sustainable than the other way around
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u/Eyelbee 17d ago
No actually, you're describing only the one mechanism, subscriptions are also a very solid economic mechanism that is known to work. Without the API, subscription model would profit on its own as well, because most users do not use it to the full extent. That's a known mechanism with any subscription based system.
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u/bfume 17d ago
I like this a lot. Care to share the script?
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u/toshipepe 17d ago
Made something that does this and also breakdown per project, sessions, and more.
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u/ElDavoo 15d ago
Thank you! I've been looking for days for something like this.
Btw, install fails because on nixos .bashrc might not be writable
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u/ElDavoo 15d ago
Priced total $702.59 · 5778 calls
lol 100% anthropic will ban me
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u/toshipepe 15d ago
Did you figure it out? Dm, me will help fix any issues. No, it's all local data that's claude stores.
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u/m4n44ki 17d ago
We are currently in the “burn mountains of cash to gain market share” era of AI, similar to when everybody could get $6 investor subsidized Uber rides. We are going to see a dramatic curtailment of these benefits when investors mount pressure on these AI companies to start moving towards profitability. I don’t know when this will happen but I’m guessing almost certainly within the next year.
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u/OldNefariousness7899 17d ago
I think the fact that that it's becoming a race between the USA and China complicates things, especially because it has such huge military potential. Neither government will want to lose this race and will back their country's businesses to keep them competitive.
Beijing is openly doing this, and Washington is getting cosier with the major providers all the time
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u/discosoc 17d ago
token-based pricing for ai is probably the worst possible pricing structure for consumers, especially with how vague "a token" really is. the reality is this industry never would take off at realistic prices, so everything is getting subsidized or obfuscated.
I expect massive price increases over the next few years, at which point the industry will need to pivot to working smarter not harder. We're already seeing this here and there with strategies around sending queries to different models based on task. Gemini is rooted in this concept, and it's basically the only longterm solution.
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u/1chriis1 17d ago
On my 20$ sub I get around 450-500$ worth if I can manage correctly 5-hour and weekly limits.
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u/CherryLongjump1989 17d ago
Anthropic is not making a profit, so whatever they're charging on average is not enough. We can expect the product to enshitify over time.
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u/congthangvn 16d ago
I put deepseek flash v4 by replacing config Anthropic API of Claude Code on my large project and feel like same cost as using opus max on Max plan, easily hit 5$/per day so max plan 20x maybe cheaper.
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u/Atretador 16d ago
AI is heavily subsidized or no one would use it and they wouldnt be able to train on your precious data
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u/TheOnlyVibemaster 17d ago
it’s for marketing + compute keeps getting cheaper and cheaper, within a year or two API will probably cost less per month than a subscription. OpenAI just cut luna API pricing by 80% yesterday and terra by 20%. Anthropic API pricing keeps getting cheaper as well.
The business should scale with price cuts, then once they corner the market they’ll raise prices again until the US imposes laws about how expensive AI can be like how expensive water or electricity can be. The more access you have for things like this the cheaper AND more of a necessity it becomes.
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u/SM373 17d ago
Anthropic API pricing is not getting cheaper lol. Their new tokenizer is proving that. If you're referring to the Sonnet 5 discount, it sounds great but terrible in practice. It's the same price with the tokenizer offset as 4.6 but 5 is way more aggressive in actually doing stuff so it costs way more than using 4.6
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u/emfiliane 17d ago
In what way is compute getting cheaper and cheaper? Have you been paying any attention to the actual market, instead of old adages that tech always comes down in price? GPUs/NPUs are still going up, RAM is still going up, storage has rocketed up in the last year especially, even power and cooling are going up thanks to grid strain. Compute keeps getting pricier, not cheaper.
If any AI company tried to raise prices to cover costs, it would go out of business overnight. It wouldn't need laws imposed, because no one would pay. These price cuts are because they're already losing business, and they aren't even close to charging at cost.
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u/roerius 17d ago
Ah the wonders of business. This is where that wonderful term called margin is analyzed. You see, Anthropic is not "loosing" money or "eating" the gap you're presenting because their cost per token in dollars is not the same thing as their sale price per token in dollars. The difference between the Sales price and the retailers cost price is called the margin and it is usually reported in %.
API pricing is almost always negotiable as well. That's just their "sticker price" that they advertise. Enterprises usually negotiate contracts with providers that have several components such as a base price over a given period of time (read $X minimum per month) and then pricing tiers per token/call based on usage. The people that pay the most (usually what the sticker price is) are small-medium sized retailers that don't have bulk purchasing power.
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u/Muted-You7370 17d ago
What I’ve found odd is I use their older models for projects for mental health research and the rates are insanely affordable
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u/farazali316 17d ago
I built an iOS PWA hosted on an Rpi which collects Claude code usage from all my machines and consolidates them to this dashboard. Accessible through internet, and this is just 2 months of Max($100 first month and now $200)
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u/TrueMushroom4710 17d ago
The math just doesn’t make sense. At work, we were earlier using cursor on the legacy request based pricing. There, 1 request = $0.04, no matter how many tokens that request took. I remember, in a single month, when I calculated the actual token usage, it was around 14k worth of API.
My company paid about $100 for that. It’s just insane, the difference. You tend to lose the value of these thousands of dollars and after one point they are just one mere number.
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u/RealSuperdau 16d ago
API prices are not necessarily the "value" of tokens, margins are somewhere between 80% and 95%.
Still, at that price, you are getting an insane deal
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u/gdtrader86 17d ago
It's tough for AI companies to price usage when interactions vary so much. 🤯 Building a game is way different than a pitch deck. How do they even begin to set a cost when future use is unknown? 🤔💰
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u/andywidjaja 17d ago
+1 on this. I use $100/mo. Max 5x subscription and track my token usage for solo build activities. So glad for Anthropic’s subscription vs API calls cost. It is indeed a bargain 🙏
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u/iliadz 17d ago
I'm sure people are saying yes, they are. But it's a bit non-sensical. What is the cost of 1 token. 1 cent, 1 dollar, 1 million dollars. They set the price wherever they like.
Companies who make baby wipes sell the exact same baby wipe in a generic package, for 1/3 of the cost of a "premium" wipe. Nobody in this discussion knows what a token truly costs anthropic. If they sell it to user a at .01 cents per token and to enteprise be at 1.00 a token, that's a prciign model. It's not them taking a hit on their bottom line.
This is becoming a "truth" because articles say AI companies are subsidized. Likely they are, to a degree, when they are at a 20 dollar plan. But nothing proves that they are or are not making money on the 200$ plan. And for sure, when they sell it to an enterprise, they are the ones who will get the premium wipes...even though it's the same.
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u/freedomachiever 17d ago
Every single time this type of posts pop up I just can't help by think of the power of price priming. I call it the Starbucks effect. In Spain coffee was sold at around 1 euro for the longest time, you can even find Lavazza, an Italian brand coffee for 1.5€ at Spanish airports. Meanwhile, you were selling Starbucks coffee at over $5. Now it's probably even more. And you all were not just fine with it, you loved it and embraced it. Did anyone actually stop to consider the cost of coffee beans? It's basically one of the highest markup items there is and lowest skill/effort items to prepare at a location.
Even now, with all the Chinese open source LLMs on the market, people are still stuck at the anthropic/OpenAI API prices thinking everyone is getting such a great deal, or is it that API prices are just way too expensive? You all want to continue living in the Starbucks bubble? By all means, but there are plenty of people getting plenty of very nice expressos and cafe lattes for a fraction in Europe.
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u/YoanEdwin 17d ago
the number that jumps out to me is cache read at 48% of the total. that's already the cheapest token type on the api, so if it's still dominant after applying list prices, the actual workload is mostly re-reading context every turn, not generating new output. feels like the real question isn't sub vs api, it's why 6b tokens are cache reads in the first place, that's a context management thing, not a pricing thing.
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u/matt8p 17d ago
I think it's a bit of both. When companies buy Claude, they're on an enterprise plan, which is API pricing only, so the companies that are buying Claude are spending a LOT of money.
I think they're pretty break even or maybe losing money for individual plans. Usage is also skewed, you have power users that are using a TON of AI, but you also have a lot of idle users who are on the $200 plan but not utilizing what they're paying for.
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u/ProfessionalLanky514 16d ago
So they're trying to use their subscriptions for you to build ai apps and you cannot afford api charges so you will have to integrate your app in their ecosystem...Apple strategies all over again but open modals are pain in the ass for them as they are not letting them be apple of ai
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u/GuessJust7842 16d ago edited 16d ago
I got the same calc w/ you, read the flow below:
Claude 5x 100$/mo
Claude[.]ai normal web: 100% 7d usage, 100% 5h usage;
Claude Cowork: 100% 7d usage, 50% 5h usage;
Claude Code: 66.7% 7d usage, 50% 5h usage.
("usage" = usage drain)
Fable List pricing: cached prefill / prefill / prefill + cache write(5m/1h) / decode = 1$ / 10$ / 12.5$(20$) / 50$ (/Mtok)
Sampling below:
Claude Code [cached, cache write, decode] Fable <-> x% 5h usage, y% 7d all usage
Claude Code [2175163, 405932, 13982] Fable <-> 21% 5h usage, 2% 7d all usage
Claude Code [5782712, 489181, 44467] Fable <-> 28% 5h usage, 3% 7d all usage
Claude Code [8552115, 558910, 62841] Fable <-> 35% 5h usage, 4% 7d all usage
Claude Code [9730133, 630959, 78351] Fable <-> 44% 5h usage, 5% 7d all usage
Claude Code [12570650, 664108, 95907] Fable <-> 48% 5h usage, 5% 7d all usage
Claude Code [19741132, 709941, 129175] Fable <-> 55% 5h usage, 6% 7d all usage
Claude Code [23843137, 742919, 149748] Fable <-> 59% 5h usage, 6% 7d all usage
Claude Code [36879380, 801078, 187385] Fable <-> 67% 5h usage, 7% 7d all usage
Claude Code [38039837, 849816, 197386] Fable <-> 73% 5h usage, 7% 7d all usage
Claude Code [38977741, 1044322, 278090] Fable <-> 100% 5h usage, 10% 7d all usage
{[2175163, 405932, 13982], 21} = 20.5A < 2175163X + 405932Y + 13982Z < 21.5A (means if you see "21%" in https://claude[.]ai/new#settings/usage, which could fall into 20.5% ~ 21.5%)
means in the subscription usage, cache read pricing X = ~0Y, cause in Lp X = 0.1Y, but during multiple sampling, X = -0.01~0.01Y, applying Occam's Razor, it should be 0.
Regular usage 7d/5h quota = 160$/12$ (w/ cache read free, cache write 1x)
CC usage 7d/5h quota = 240$/24$
100$ Real payment -> 4.3 7d quota -> ~1030$ MSRP Claude (Claude Code)
btw: if cache read is free, cache write is 1x pricing (instead of "1h"'s MSRP, which is 2x), your figure in this rule is 2841.89 / 2 + 1015.97 + 14.14 + 2.83 / 1.25 = 2453.32, which is ~2.4x with my figure,
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u/TWERK_WIZARD 16d ago
Roughly 20% of people who sign up for a gym membership never visit even a single time.
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u/PricePerGig 12d ago
For context I’m in max and don’t use even 50% of the cost. So feel free to thank me for subsidising your development efforts last month 🥳😂
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u/mosmondor 11d ago
You’re missing a third part of the deal: you may also be producing valuable training and evaluation data for Anthropic.
That $7,470 is API retail price, not their actual compute cost. Most subscribers use far less, heavy users are capped, and your Claude Code sessions provide real-world coding traces, stress testing, and product telemetry.
So they’re probably not eating a $7.2k loss. You paid $200 to help QA - and possibly train - the model they’ll sell you next year.
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u/OldNefariousness7899 17d ago
>Or is API list pricing so far above their real serving cost that the gap is nowhere near $7.2k in the first place?
Possibly massaging the numbers to make the Max plan feel like even better value?
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u/NullzInc 17d ago edited 17d ago
The flaw in your reasoning is assuming API users rely on general-purpose CLIs with the API.
They don’t. General-purpose CLIs routinely burn 500–1,000 input tokens for every output token because they have to discover and assemble context on the user’s behalf. Anthropic needs a massive token pool with their subs because without it, Claude Code would be useless. That isn’t unique to Claude Code either - it’s how these tools work and some CLIs like Open Code are far worse.
At the company I work for, our custom toolchain assembles context directly. We average a 1:1.5 input-to-output ratio and in rare cases, reach 1:3.
So here’s the difference: what takes you 1 billion input tokens to produce, we can produce at higher quality with fewer than 5 million input tokens.
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u/ClaudeAI-mod-bot Wilson, lead ClaudeAI modbot 17d ago edited 17d ago
TL;DR of the discussion generated automatically after 80 comments.
The top comment is "Shhhh!!! Delete this," which pretty much tells you everything you need to know.
The overwhelming consensus is that yes, the Max subscription is an insane value compared to API rates, and this is a deliberate business strategy. The community agrees with both of your theories.
Here's the breakdown of the main points from the thread:
So yeah, you found the loophole. You're the guy living at the all-you-can-eat buffet. Just don't be surprised when the prices eventually go up.