I recently switched off Max flat rate to Enterprise API pricing and I went from 200/mo to 10k/mo with the same usage pattern on Opus. They don’t offer flat rate to enterprises.
So Fable would cost me 20k/mo at Enterprise rates. That’s around the average cost of a loaded SWE in the USA. “But I’m >2x more productive” doesn’t justify doubling the opex of the Software/IT department for most companies when revenue isn’t even up 10%.
I switched to DeepSeek v4 Pro with OpenCode and am on track for a few hundred dollars of spend this month.
Rewriting your stack from Ruby to Go in 2 days where it would’ve taken 6 months is impressive and fun. But that isn’t upping revenue.
Iterating on net new business features and ideas that are niche that the LLM isn’t trained for are much harder. Is 20x the token cost worth it there?
I don't live in USA. I'm getting paid around $2500/month and that's good salary for developers here, plenty of folks are getting below that number.
So this pricing is just completely outside of our economics and nobody I know would pay that, no company will justify spending $20k/month when they can hire 10 more developers instead.
It is very interesting unfolding of events. Can't wrap my head around it completely.
Not justifying AI expenses, but $2500/mo could easily cost employer close to 5000$/mo depending on country.
Not doubting this at all but could you (or someone else) break this down for the sake of my curiosity?
I understand pension contributions, but what are the other "hidden" costs that could equal the net salary?
Example from Germany: Employer also pays a share of health insurance, unemployment insurance, public pension and elder care insurance.
This is not visible on your payslip, i.e. if you earn 5k€ brutto, the employer has to pay these shares on top of that.
But that is 20% not 100%. And in most non retarded countries brutto is actually brutto, because there is no need to lie to people about how much the government takes away
The 100% figure is coming from the comment above mine, actually. As for the rest of your comment, your assessment is noted.
Historically, this has nothing to do with lying, but is all about the founding idea of the social security system that all parties (workers, employers, state) carry part of the burden. Employers were supposed to pay their fair share because they also benefitted from the system (a sick or injured employee is not a productive one). Or saying it differently: the employer pays an insurance premium to reduce the effects of sickness. That premium is tied to the „value“ of the employee as measured by their salary.
There is plenty to improve with the system but to call it „retarded“ considering how much good it has brought to the world seems quite wrong to me. I don’t want to work in the pre-Bismarck era
In the UK, a £45k/yr employee pays their own tax and gets a take-home of £35k.
The employer pays £6k for National Insurance (atop the employee's NI contributions). Pension: 2-3k. Apprenticeship levy is £300. 3yr-amortised recruitment fee is £4000. Hardware costs: £1000. Office space £5000. Software/tools: £2500. Benefits: £1500. Training: £1000. Other admin overheads £500.
You pay that person for ~250 working-days, but they only attend for ~220, due to annual leave and sick pay, so you get around £62k worth of attendance out of that person in exchange for £70k, of which the employee sees £35k.
a more honest way to look at it would be that the government gets 50% of the employees total expense to the company, so it is basically 50% income tax
A quick google tells me that software devs usually count for 20% to 40% of the total workforce in a software company. The rest is overhead that increases with every added dev.
And if one were to compare cost of a dev vs cost of an LLM, the dev comes with the cost of workspace, computers, sick pay, summer party, conferences and etc etc.
In the US, over and above salary, payroll taxes add 7.65%, pension contributions might be up to 5%, and employer healthcare and other insurance contributions can be in the thousands, plus other benefits, equity compensation, and per-employee software licensing, and lots of people just estimate 2x salary as the “total cost” of an employee, although that probably overstates it a bit.
In the UK, employers pay a stealth tax of 15% (recently increased from 13.8%) on top of the quoted salary minus the first £5k (recently decreased from £9,100.)
So your "£50k" salary actually costs your employer £56,750, and that's before all the other expenses mentioned elsewhere in this thread such as hardware, office rent etc.
In Sweden I always heard the figure to double the income of the person to get what the company actually pays, including taxes and "employers fee". I know this has gone down a lot in recent years, also not sure if it was ever exactly true, but likely very close anyway.
Hitting the first calculator I found gave me 50 kSEK costs 69 kSEK. So far from double nowadays.
I'll add a concrete example from a not-too-cheap-anymore EU country: Estonia.
* Average software dev salary in Q12026: 4945€ / month [1]
* Total cost for the employer: 6616.41€ [2]
For $20k/month, you'd get 2 x full time mid-level developers + 1x junior dev or QA.
So the calculation becomes: which option can produce better results for your specific use-case, "you + Fable" or "you + 2x mid-level developers + 1x QA". (and from personal experience, mid-level in Estonia = senior dev in the US, in terms of skillset and experience.. but YMMV)
(Of course that's simplified. Your full time devs need _some_ level of AI subscription as well + hardware so add a couple of hundred to their salary per month etc so you might only be able to afford 2x mid level devs, instead of 2.5)
[1]: https://palgad.stat.ee/en
[2]: https://www.palgakalkulaator.ee/en
I'm currently working for an Estonian startup and we pay quite a bit more than that. We hire remote (primarily across Europe) and our biggest issue is finding the right people. You need to consider AI can be "hired" or "fired" instantly too, so it's better to compare it to contractor rates, which start at around €350/day or €7000/mo (20 working days) in Europe.
(Our team spend on AI devtools comes out to around $1500/person/mo)
Sure, we pay above market rate as well :) Doesn't change the fact that the average across Estonia is as stated :)
Well you can just scale your AI employees up and down as much as you want. Companies already pay a large premium for freelancers just to be able to fire them on a whim, so spending 5-10k a month on something that more than doubles the productivity of a senior developer might be well worth it as you can just adapt spending based on your business needs. If you can deliver a feature that lets you write a 100k invoice with 10-20k of tokens within a month or have a senior dev crunch that out in 6 months instead I think it's clear who wins. It's all about money and the AI companies know that, they have their pricing down exactly to sit in the sweetspot where it hurts just enough that companies can still afford it but not enough that they would look for cheaper alternatives.
- Total cost for the employer: 6616.41€ [2]
This is a good start, but the calculation doesn't include office space and overhead (for every 100 developers there is maybe 5-10 support staff to cover the additional legal / administrative, and don't forget the extra cost in supervisor time to manage them)
Exactly, that's why I wrote that it's simplified and the actual full cost to the company depends on your company size and setup (fully remote vs in office, management heavy vs lean-flat etc). One point though, from personal experience, I'm spending an order (or two) of magnitude more time in "managing" an agent than I spend in managing employees - so that part might come out cheaper in the end for having actual employees ;)
> no company will justify spending $20k/month when they can hire 10 more developers instead.
one big enough to license the model and self host on existing infra.
Hiring 10 more developers comes with its own set of difficulties and additional overhead
now if only onboarding people was as easy as onboarding the bots is getting
I think you are broadly correct, but just to pushback on a few points: (1) Ability to solve hard problems in days vs weeks as immense value (2) Back-end improvements (if done right), should improve platform speed, stability, scalability etc. which should have revenue implication (3) Ability to on-board a SWE equivalent entity in minutes, have them work on a specific hard problem and then off-board them in minutes can have value
All of the above, of course, depends upon Fable consistently being a 2x-3x SWE at minimum.
>pushback on a few points
Claude keeps telling me this when I argue with it. LMAO.
“gently push back”
> Back-end improvements (if done right), should improve platform speed, stability, scalability etc. which should have revenue implication
Depends entirely on the domain. If you're selling entreprise software, this kind of stuff barely matters for sales.
It can reduce operational costs which is good but there's a limit to how much that's worth.
Yep, there are many, many, non-niche domains in which this doesn’t mean much at all.
“Ability to solve hard problems in days vs weeks as immense value”. Citation needed.
LlMs are incredible don’t get me wrong, but they are good on tiny contexts (writing a script). Not on software engineering (adding features to Chrome).
Honestly, LLMs been OK at adding features to software since around Opus 4.5. From what I've tried of Fable, it's a decent step up from the Opus models and I can only see things getting better.
You're not really solving problems, you're retrieving the best match of solved problems from compressed corpus. And that corpus is available to many companies, meaning "hard" problems stop having "hard problem" value the moment they enter the weights of any model via the internet ... or distill from one model to another. Anthropics business model is commoditising knowledge, but as we see with the Fable model card, they only want it done to the knowledge of other businesses, in their own field, they totally hate it.
I don’t think that’s an accurate or useful characterization of modern AI like Claude at all. It is not simply regurgitating knowledge. It applies its knowledge to create bespoke solutions to the problem you pose to it, and is able to self evaluate its progress towards the completion criteria. If you don’t think that counts as “problem solving”, your definition would exclude nearly all knowledge work and engineering.
> It applies its knowledge to create bespoke solutions to the problem you pose to it, and is able to self evaluate its progress towards the completion criteria.
It imitates applying knowledge. The imitation may be uncanny, but assigning LLMs intentionality and ToM is a category error.
Indubitably, computably.
Does "applying knowledge" necessitate human-like intentionality and theory of mind? If you insist it does, and this is a category error, then we need a new category.
By analogy, consider that many have referred to classical, deterministic computing as some kind of "thinking" for the last half century+. Does this stop being kosher when the computer has an uncanny propensity for human language? Perhaps, but the computer is still clearly chewing through problems that would have required a lot of human thinking (e.g., arithmetic) in ages past.
I haven't seen any genuine proposals for words to replace the human mind analogues, let alone proposals that the anglosphere would plausibly adopt en masse.
People underestimate the vastness of training data (internet) and overestimate their ability to recognize if something is really bespoke. Not to say the no problem solving is happening, because there are many problems that we inefficiently solve again and again and the LLMs are making the solutions more accessible to everyone with a subscription.
It’s like saying you can’t make a unique sentence unless you first make unique words
> You're not really solving problems, you're retrieving the best match of solved problems from compressed corpus.
This is not correct. LLMs interpolate in a high dimensional space, so you're actually composing the best matches in a compressed corpus to find novel points/paths in that space. That is problem solving.
In my experience, the challenge in software development is not to solve a problem, but to define the outcome, the scope, the acceptance criteria etc.
Exactly, this is the hardest part and the reason why many projects fail
The thing about AI-generated “solutions” is that they often go down bad rabbit holes and need to be re-run, or since they are so “cheap” to create they are often just thrown away and rebuilt when requirements evolve. Plus, just more stuff is created and needs to be maintained. So in the end, your efficiency gains go out the window.
20x the cost means you need to have fable to be 20x better than the alternative, which is a tall order. And there's more options out there too, perhaps the 4x cost is enough.
This means if the deepseek / under 1k alternative is at least x1.2 improvement, fable needs to be x24, which I think is very2 unreasonable. It is possible for it to worth if it can x2 a $20k SWE, though I doubt it can do that.
I work at a smaller tech company (<300 people), and my friend showed me everyone's spending.
Our top user is at 10k a month, but the next highest is $2,000.
I would say the average is around $1,000-$1,500 for a developer.
We have completely unrestricted access to Claude, Codex, and Cursor.
Funny enough, the guy spending 10k is not even a dev by trade but an SME in what we work on that just vibe codes apps and somehow has not been cut off yet lol.
I have a single thread of GPT 5.5 medium running basically all work hours and I am around $1,500 a month in spend on Enterprise pricing.
At my company, most devs are under $1500 a month as well.
I’ve heard of a few cases of devs racking up bills fast, but it has typically been due to inefficient context usage. Like they just have one super long session with Opus 1M and are getting killed with input token costs and cache misses.
With careful context management and some thought into good approaches to problems, I have personally only rarely even hit $1k in regular use.
Interesting! Would it be fair to say your company spend $100k to $150k per month on this?
Multiply this times many, many companies, and you can see how providing AI could theoretically be a good business to be in. Margins may be tight, though.
Also -- I'm convinced someone will figure out more use cases beyond software programming, which will result in many more companies spending $1k+ per employee per month.
It remains to be seen how much of this is a bubble.
> Funny enough, the guy spending 10k is not even a dev by trade but an SME in what we work on that just vibe codes apps and somehow has not been cut off yet lol.
I'm guessing he's producing pretty valuable work. We have a few SMEs that vibe code tons of stuff with Claude. The only thing they really need tech for anymore is deployment and helping get their wheels unstuck on occasion.
>I switched to DeepSeek v4 Pro with OpenCode and am on track for a few hundred dollars of spend this month.
I was about to say that. Deepseek is just magnitudes cheaper and absolutely good enough for most things. Anthropic and co just try to milk the cow while its possible. If they cant compete with Deepseek pricing I do not see a bright future for them.
Not only Deepseek, other providers such as Xiaomi MiMo are excellent as well and offer fast token modes and other perks.
Its too bad my boss views China as the big evil country so he wont ever make the switch to Deepseek but then proceeds to throw all our data to US companies like OpenAI or Anthropic...
There are US providers for DeepSeek v4, MiMo 2.5 and GLM 5.1.
Does the location help though, if the company isn't trusted? I can't even visit the webpages of these companies from my enterprise network
And even if so, I'll try to get rid of any US affiliations within my workplace, so US providers are not an option either.
There are also EU providers for those models, e. g. Tensorix.
I'm speaking of third-party providers. They just host those open models themselves on their hardware.
But those US providers AREN'T CHEAP like the Chinese ones are (for the big, actually useful ones, like 1.6T+ models)
> Is 20x the token cost worth it there?
No it doesn’t and will not be. Companies have not realised the cost yet, wait till the end of the financial year and you’ll see a different direction.
DeepSeek v4 is pretty decent, and probably on par with sonnet. I see a future of hybrid models where opus or fable might be used only for complicated features or bugs, but general day to day would be DeepSeek or whatever good models that will be released later.
I recently switched off Max flat rate to Enterprise API pricing and I went from 200/mo to 10k/mo with the same usage pattern on Opus. They don’t offer flat rate to enterprises.
So what keeps your management from just buying everyone individual flat-rate Max subscriptions, or at least buying them for the users responsible for the sky-high token invoices?
I see a lot of comments like this but I don't understand why some people willingly pay so much more than others for the exact same service. What are you getting that I don't get as a $100/mo Max subscriber?
Zero data retention policies.
I get that with Max. (And nobody gets it with Mythos/Fable.)
> So Fable would cost me 20k/mo at Enterprise rates
That's enough to buy a house in my country...
Eventually solving for cost is a much easier problem than solving coding.
With GPT 5.5 on the $100 plan, it's hard to hit any 5h/7d limits - while allegedly being better than DeepSeek 4 pro. Not sure why, or how you spend "a few hundred dollars of spend".
With that said, I still had the Pro plan on Claude, I didn't expect much, but it blew up my 5h allowance on Fable with one simple single prompt, and it didn't even complete lmao
I'm on $200 plan which is supposedly 20x usage of $20 plan. With few Fable prompts (I'm working on u-boot port) I got 10% of my 5h usage, so that's already 2x of $20 plan usage and that would be 40% of $100 plan.
So Fable is just not usable for $20 plan and barely usable for $100 plan.
Important to note that both OpenAI and Anthropic do not allow the subsidized monthly subscriptions for enterprises.
Companies have to pay monthly for the harness app (codex, claude code) and the tokens are priced separately based on standard API pricing.
It's not just Pro! I have Max 5x and Fable absolutely blew up my 5h window. Didn't complete the code review either, and got downgraded back to Opus 4.8 on the really important memory safety parts I actually needed it for. It's an excellent model but Anthropic's not providing a good experience.
Do you understand that, for 10-20k a month, you can hire 1-2 senior engineers AND give them Claude subscriptions?
will they be a better investment than your current staff engineer with fable token allowance?
Are you seriously asking if employing people, for the same cost, is a better ‘investment’ than relying on LLMs? Jesus Christ.
I am because CEOs are. Look where the puck is going. Sorry to update your p(doom) priors in this way, it was obvious to anyone paying attention years ago conditioned on uplift trend persisting. Trend persisted and here we are.
Welcome to the new world. People start to repeat what tech founders preach. They do not require humans in the mix. Peter Thiel gave a good example of that mindset in a (mostly) recent interview where he didn't have an answer on "Should humanity survive?"
https://youtu.be/ngtp3v1_nCI
I’m asking this question right now.
If I was offered another dev on my team or their salary in Claude credits, and told to meet a deadline with a gun to my head, I’m taking the credits.
Yes. Hiring people has various benefits, I will lay them out for you:
- They learn the domain of your product, which means long term ownership and knowledge establishes itself. If you've only ever shipped SaaS slop, you might not know, but lots of companies are solving real world problems that have no better solution. Owning and understanding the code and the domain is key.
- They will learn from their mistakes (no LLM does this).
- Human skill is a REAL moat. Once you build a team that fully understands and is skilled in the domain you work in, these people are going to be the thing that sets you apart. If some of them are particularly social or charming, let them sit in with you for meetings and watch them provide loads of value, for no added cost.
- If Claude or OpenAI is down, they will continue thinking. In fact, they will continue thinking even when off the clock! This is a neat little hack called "consciousness" where you get a lot of work for free!
- You can hire people who punch above their weight; not everyone you hire needs to be a 500k/year staff software prime engineer of doom, you can just spend some time and effort to hire good juniors/competent mediors who will think for themselves (gasp!) and get work done.
- You still get ALL THE BENEFITS OF AI!!!! They can use AI just like you can, or better!
- You get people who you can brainstorm with, which is distinctly different from LLMs because your employees are less likely to want to suck you dry in every sentence just to make sure you spend more tokens. Employees don't care if you love them, they care about the quality of their work if you manage them correctly and reward that.
- They are quite loyal if you treat them right; spend a little more on their well-being, and they will stick around, come in to work every day and deliver cool things with you.
- Humans can only manage, review and give tasks to so many agents. If you add more humans, you can handle more agents.
An expensive LLM and a lot of extra tooling gets you some of this, yes, but not all of it. With humans you can still do the expensive LLM and extra tooling if you end up making enough money anyway.
I’m sorry sir this is HN, your post is too sensible.
- AI works 24 hours a day
- AI isn't bound by need for rest, vacations, sick days, or labor laws
- AI doesn't bounce from company to company, taking your business knowledge with it (actually this isn't technically true based on the practices of AI companies, but that's not a technical requirement)
- AI doesn't join a union and stop work in demand for higher pay or workers rights
This is what CEOS and capitalists are thinking. For capital, the best outcome is to not have any labor at all. And if you can do that when your competitors can't, then you have a huge market advantage. (Slop notwithstanding)
I'm not saying this is a "good thing" but this is what drives the market. Less labor revenue in the long term and money printing machines.
The issue is, of course, that the quality of work is not good, and this will eventually show itself, likely in the total collapse of the US economy, but until then I wish them good luck with this.
The US economy has survived 40+ years of buggy, no-automated-tests, no-version-control Excel spreadsheets. I think it will survive this too.
The difference is that bad untested excel spreadsheets didn't get trillion dollar valuation.
why would you expose to a company what are you working on, in what way and on what research?