That site offers substantial free tokens, is often reported as being flaky and their affiliate links are popping up on different social medias but look sketchy as anything.
I know of a friend's company in India who purchased inference, at 4% of the actual price and states that it gave him an unbeatable competitive edge in their large running video influence pipelines. Any new competitors could not offer their pricing at all.
Primarily that operated because registering a new company getting free AWS credits was a very tiny cost
How would one even word a bulletproof subscription contract for agentic tokens, anyway? You can't forbid automation because sub-agents are automation. You could forbid "using tokens for the benefit of more than the human who signed up" but then what do families (especially with kids) need to do? What if your friend asks you a question and you turn to a chat model? Forbidding "reselling" tokens outside of a household sounds like the closest terms but that's leaky for anyone who travels a lot, etc.
Fixed cost per token simply works.
I disabled automatic downgrading/rerouting because it sometimes takes me a second to tell when the answer came from a different model than I wanted. You could easily sell Opus as Fable for a good while.
It turns out to be a pretty complex program to solve at scale. Token fraud is a lucrative market and the adversaries are surprisingly sophisticated. It's a cat-and-mouse game, accelerated with AI.
(If you'd like to work on this, we are hiring :))
imagine ford starts renting out company cars at a huge discount so they can get people to buy the same model for themselves after they drive it at work. its the exact same car and costs the same amount to make, they just take a loss on it and use by anyone other than employees is banned in the contract.
some small company realizes they dont really use their cars that much so they rent them out again for 3 days a week to get some extra cash. is that fraud? it costs ford nothing because they get the same payments either way, they just lose potential profits. they are the ones who decided to set up a loss leader and take the risk of someone "abusing" the system so we dont need to use public resources to defend their strategy. that wastes taxpayer money to protect corporate profits, and it creates moral hazard because ford (anthropic) is not the one paying for enforcement.
Not unlike narcotics being cut with filler
Here are the two open source proxies listed in the article: https://github.com/songquanpeng/one-api and https://github.com/QuantumNous/new-api
i think this alone is the biggest bear signal
"$0.13 of usage per $1 spent"
So I spend a dollar and I get 13 cents worth of usage?
I guess it means the otherway around but I'm not seeing how that phrasing works. Are they paying a premium to access US models?
Do these numbers make sense? $0.13 usage per $1 spent?
1. Tokens are model-specific: e.g. tokens used by Anthropic cannot be used in models of other companies.
2. Tokens are generated by GPU cards. They measure the power of GPU cards.
3. Tokens cannot be separated from the models. You sort of "connect" the software part (models) into the hardware part (GPU cards) to use the tokens generated from the hardware.
The problem is loss making subscription as a marketing tool. But if you do loss leaders that be the risk you take.
No wonder social media is so shit nowadays. All that brainwashing and propaganda from third world countries, now at 4% the price!
I have some past experience with subscription plans for a much less interesting product. Abuse is inevitable. As you do your math on the subscription costs you look at the actual usage across all accounts, which includes the abuse.
Cleaning up abuse was still a priority because it meant we could give more service to the real customers. It's a frustrating battle because you actually want to give good service to the real customers, but you also want to let each account do as they please with their susbcription. That latter priority probably fades fast for something like an LLM company when you discover that the abuse has become automated and is scaling up so fast that it's tilting the math toward degrading service for everyone.
> Fixed cost per token simply works.
As a consumer, I benefit greatly from the subscription rates. There's a lot of grumbling about how they should go to fixed token for everyone but I'm over hear happy with the subscription plan offerings while they last.
reverse the pricing structure; give modest discount once you go over certain amount of tokens, then you are incentivized NOT to start multiple accounts.
require first few transactions to be pre-paid to get around at least some of the card problems.
Of course, that would fuck over subsidized plans, but I don't see any option to keep them if you want to avoid the flood
Client-side detection can always be sidestepped, and you need to intermediate the actual inference to get enough signals to make an accurate prediction. There are hundreds of listings for cursor tokens/credits right now.
We use canary values to detect the resellers, and I believe that's the only approach that will actually work at scale.
This is more like sharing Argentinan $2/m Google Premium subscriptions via a load balancer.
What OpenAI and Anthropic are selling — a flat-rate subscription with both 5-hour and weekly rate limits — is a bit like an all-you-can-eat buffet.
They expect some customers to generate more in costs than they bring in revenue, just like some people at the all-you-can-eat buffet eat more than they pay for, but by the law of large numbers, the mean cost per customer comes out to something the labs are comfortable with.
What the resellers are doing is undermining the labs' assumptions that every person needs to eat and sleep, and hence won't use every 5-hour window to the fullest. It's the equivalent of buing the all-you-can-eat pass for one person, coming into the restaurant with three of the largest suitcases you can find, and filling them to the brim with food, which you later re-sell at much lower prices. In other words, fraud.
I mean, in a more accurate analogy, Ford would be paying for the petrol too.
Inference is expensive and Anthropic did not agree to provide inference to some random third party so that the subscriber can make a few extra bucks.
Most likely, yes.
There's a common fallacy that once you pay someone for a service, you are free to do whatever you want with that service. In the case of the rental car, the contract the company entered into would prohibit reselling the services and limit who can drive them and for what purposes.
Some people see these limitations and scream "Not fair! They paid money, they can do whatever they want!" The misunderstanding is that the price they paid was predicated on the specific use. They got a lower price for the rentals because the provider calculated the expected use case and priced it according to that.
If the small company starts renting out the cars to try to maximize how much they're used, that breaks the financial model. That's why this type of use is forbidden in every basic rental contract.
It's the same reason why you can't rent an apartment building and then turn it into an AirBnB. On a smaller scale, it's why you can't go to an all-you-can-eat buffet and load up on food to carry outside to your 5 hungry friends. This type of pricing is everywhere.
There is a vocal online minority who believe user license agreements shouldn't be enforced and individuals should never be considered accountable for following them, but that doesn't even apply to these resellers. This isn't a lowly individual user trying to get back $10 from their $20 per month plan that was going unused. There's no way to even achieve the scale and discounts without mass, automated fraud. They're doing chargeback fraud or using stolen credit cards.
It's not even a crime where the big corporation is the only victim. The higher the volume of fraud on the subscription accounts, the less real usage you and I get for our dollar. These people are jumping on the accounts targeted to individuals like us and abusing them to sell tokens to big corporations trying to abuse them at scale. People like you and I lose when these accounts get their limits reduced or the companies start introducing ID checks and KYC just to use basic services.
There are quite a few other mitigations that could be done by providers that aren't mentioned in the article.
GPUs "generate tokens" in the same sense that human feet "generate steps"
You can't compare token counts across different providers to get an absolute measure of "total work done" for the same reason that you can't compare step counts across different people to get an absolute measure of "total distance traveled"
You should do a bit of reading on what a token is. The short answer is that it’s a series of 2-4 bytes of information turned into an integer.
Your comparisons are akin to asking “are amazon gift cards the same as a bunch of pesos?”
Is this some kind of attempt to make the other side look better by making the worst argument you can?
I don’t know if that’s true of India or not, but I like to give comment authors the benefit of the doubt that being specific about the geography was helpful context here
At Fusion Festival, I saw a big bulletin board completely covered in notices of "we tested this pill, here's a photo, here's what they thought was in it, here's what was actually in it"
They also spelled the name of the charity wrong on all the maps, so that's nice.
Case in point: OpenRouter is serving 60T tokens a week, but this is all human text and code (and cache hits!), which is almost certainly compressible enough that you could fit the whole week’s usage on a single hard drive.
[1 ]https://openknowledge.worldbank.org/entities/publication/130...
In the example above, part of signing the contract is agreeing that your usage of the vehicles doesn’t involve reselling them. Signing that contract with intent to re-rent them is a very clear legal problem.
There are several other layers of problems. When you rent something to someone else, you are representing that you have legal standing to rent it out.
If you rent out someone else’s property after agreeing to a contract that says you cannot rent it out, you are doing some more serious misrepresenting of the key facts and your intent. It could also trigger laws about theft of services depending on the situation.
This is about controlling who gets to use the tokens for what, not about payment fraud.
At $1 of usage for $0.13, the reseller is making a tidy profit on top of whatever subscriptions they're reselling.
I assume most of it is just people who want cheaper access to these models and don't mind subsidizing access via somebody who is simultaneously distilling the model.
This is about people circumventing the model company's attempts to protect their intellectual "property" (which, if you insist on that incoherent usage of the word "property", they themselves stole from the rest of us).
It's equivalent to buying a DVD in the US which is region-locked to Asia. Grey market, not black market. If you use a stolen credit card to buy that DVD, well tat's a totally separate matter.
threat-research llm-security
June 28, 2026 Matt Lenhard 9 min read
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I’ve spent a lot of time thinking about token fraud, a problem I first stumbled upon while working as a software engineer on an AI gateway.
We faced constant abuse. At first it was free-credit abuse, where users spun up accounts en masse. Then it was our support chatbot. I started talking to friends about it and hearing stories of companies losing millions of dollars to abuse each day.
The abuse took a number of different shapes, and the abusers were relentless. I came to realize that the problem was much bigger than us. A new form of fraud had emerged, and it had become endemic to the token economy.
While researching where the abuse was coming from, I stumbled onto a Chinese forum where operators openly discussed the relays and their methods. My notes on the industry and its players are below.
A relay — or “transfer station” — is essentially a service that proxies traffic to U.S. models, often at a deep discount. For example, one operator’s price-comparison site listed a package that bought the equivalent of $3,333 worth of official Anthropic credit for 425 RMB — roughly $0.13 of usage per $1 spent.
Effective rate
$0.13
of official usage per $1 spent
Sample package
$3,333
of Anthropic credit for just 425 RMB
Top discount
97.8%
off official pricing, at the cheapest relay
To make that concrete, here’s how far below official pricing the relays we track actually run, ranked by discount:
The ecosystem runs four layers deep, from the merchants sourcing raw accounts down to the developers buying cheap tokens:
01 Upstream 卡商 / 号商
Card & account merchants — virtual credit cards built to pass U.S. and European billing checks, plus bulk-registered accounts.
02 Midstream 账号池
Account pools — aggregate hundreds of upstream accounts, manage tokens and rate limits, handle failover, and expose a single API.
03 Downstream 中转站
Relays / transfer stations — wrap the pool's API in a clean, billed, Chinese-language product and compete on price.
04 End users
Developers, startups, and SaaS chasing cheap inference — plus commercial buyers running model distillation.
Sitting at the top are the card merchants (卡商) and account merchants (号商). They sell virtual credit cards designed to pass U.S. and European billing checks, along with bulk-registered accounts.
In the middle sit the account pools (账号池). A pool aggregates dozens or hundreds of upstream accounts, manages their authentication tokens and rate limits, handles failover when accounts get flagged, and exposes a single API surface that downstream relays can consume.
The inventory isn’t only model-lab accounts. Alongside direct OpenAI, Anthropic, and Google credentials are accounts harvested from the application layer.
Much of the forum’s activity centers on “reverse-engineered” access to tools like Kiro and antigravity, which are consumer products, not lab APIs. To a pool, it makes no difference whether a token comes from a lab or from an app built on one; anything that resells or exposes a model is a target.
Downstream sit the relay / transfer stations themselves — the consumer-facing layer. They wrap the pool’s API in a clean Chinese-language product, handle billing and invoicing, run customer-support WeChat groups, and compete on price.
At the bottom are individual Chinese developers, small startups, and mid-sized SaaS companies hunting for cheap inference — as well as some larger commercial buyers using the infrastructure for model distillation.
In practice these layers blur. Many operators run both the pool and the relay, and the forum’s own participants often use “pool” and “transfer station” interchangeably.
Almost every relay I’ve looked at runs on one of two open-source projects: one-api or new-api.
Both are OpenAI-compatible gateways. An operator deploys the panel and adds a set of channels (渠道). Each channel represents a provider plus a pool of API keys. The panel exposes a single endpoint that matches the OpenAI API, so buyers just point their existing SDK at the relay’s URL. On every request it pulls a key from the pool, forwards it upstream, returns the response, and deducts quota priced by usage times a multiplier (倍率). It manages the users, tokens, pricing tiers, logs, and billing.
new-api is a more actively developed fork of one-api, and the difference is mostly commerce: it ships with self-service payment and recharge, plus image, video, and audio models. Across the relays we track, one-api turns up roughly four times as often as new-api; the original base is the more widespread of the two, even if new-api is the one built to sell.
There’s nothing inherently illicit about the software. one-api and new-api are neutral, legitimate tools. Plenty of companies self-host them to put their own accounts behind a single gateway with team quotas and spend tracking. A relay crosses the line when its channels are stocked with stolen, leaked, or pooled keys instead of the operator’s own, and when it resells that access against the providers’ terms.
The three main use cases seem to be cheap tokens, getting around geo-restrictions and model distillation. A few relevant quotes from the forum:

From the V2EX thread · translated

From the V2EX thread · translated
I was surprised by how mature the market already is. There are price-comparison sites for the relays, affiliate programs, and even gateway products. On the forums, consumer demand looks just as strong. And these aren’t fringe operations: the ten highest-traffic relays we track pull a combined 3.6 million visits a month between them.
My hunch is that things get worse for the application layer from here. As Anthropic and others roll out KYC controls and identity verification, the abuse won’t disappear, it will just move somewhere else.
A clear sign of how normalized this has become is that one of the relay directories runs a daily lottery for API keys.
The site — hvoy.ai, which otherwise bills itself as a relay authenticity checker and price-comparison tool, gives away fifty $100 API keys every single day. You earn entry credits from a daily check-in, spend 20 credits per ticket, and can buy up to three tickets a round. On the day I looked, 258 people had entered 401 tickets for the fifty keys.

hvoy.ai · daily draw for 50 × $100 API keys
Every day
50
$100 API keys given away per round
Cost to enter
20 pts
earned free from a daily check-in
A recent round
1,150
tickets competing for 50 keys
The part that got me is the fairness theater. The draw is provably fair — the same cryptographic scheme legitimate crypto-gambling sites use to prove they didn’t rig the result. The random seed is the hash of the latest Bitcoin block, winners are picked with a Partial Fisher-Yates shuffle, and the full list of entries is published as a snapshot before the draw.
I’ve talked to many companies facing this, and the truth is that there’s no clean fix. Fraud is a constant cat-and-mouse game. What follows isn’t a silver bullet — it’s the set of things that I’ve seen work and that others are doing, roughly in the order that abuse travels: from account creation, to detection and then to damage control.
Assume some abuse gets through anyway, and limit what it can cost you:
And when you do catch someone, throttle quietly. A clean error just tells the attacker which signal to fix before they come back.
None of this stops the abuse for good. But if you make attacking your own service expensive enough that the numbers stop working, they’ll try to find an easier target.
All quotes are translated from a V2EX thread in the site’s Programmers section, “A comprehensive guide to AI transfer station jargon,” started by the user v2exgo (who operates the relay at terminal.pub). The thread ran from March 5 to June 23, 2026 and drew roughly 35,000 views and 190 replies. Reply numbers below refer to that thread.
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