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Would you trust a cheap unofficial AI API?
WTF is a transfer station?:
A transfer station is a third-party API proxy. You send your AI request to the proxy. The proxy forwards it to Claude, Gemini, or another model, then sends the answer back.
The problem is simple: the proxy sits in the middle, so it can see the request, the answer, the tool calls, and sometimes the work your coding agent accepts.
Claude tokens are expensive.
For builders in India, the dollar price hurts more.
So when someone says "same Claude, 90% cheaper," the first reaction is practical:
Why pay full price?
Chinese developer communities use unofficial API proxies to access Claude at prices as low as 10% of the official rate.
The discount is the visible part. The serious part is what happens to the work passing through the middle.
If you use a cheap proxy for normal chat, it can log your prompt and the answer. If you use it for agentic coding, it may see repository context, tool calls, file names, error messages, code changes, and the final answer you accepted.
That is more valuable than a random prompt.
I am Alex, welcome to ShortCu8 by Innov8.
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⭐Today's Shortcut
Treat every unofficial AI proxy like a public upload box.
Before sending anything, ask:
Who receives the prompt?
Which model actually answers?
Where do the logs go?
If you cannot answer those three questions, do not send private work there.
The discount has to come from somewhere
ChinaTalk describes the Chinese transfer station economy as a layered market. Some operators get access through account pools, unused quota, subscription sharing, discounts, or other account sources. Then they resell API access through a proxy.
That can explain part of the discount. The stronger claim is that logs may be the real business.
Every request through a proxy can sit on the operator's server. For coding agents, that log is more than:
"Write me a landing page."
It can include:
the task you gave the agent
the files it inspected
the errors it saw
the fixes it tried
the final code you accepted
That is training data with a useful label attached: the human accepted this.
For companies trying to train better coding models, those traces are valuable.
ChinaTalk is careful on one point: the exact resale chain is not fully verified for every proxy. Keep that nuance. But the incentive is clear. If the proxy can sell cheap access and collect training data, the user is both customer and supply.
The model may not be the model
There is a second problem: you may not get the model you paid for.
The CISPA paper "Real Money, Fake Models" audited 17 shadow APIs and found evidence that some services did not behave like the official models they claimed to provide. Simple example from that research: API access marketed as Gemini 2.5 Flash scored far below the official Gemini 2.5 Flash API on a medical benchmark.
That matters because a cheap proxy can show a premium model name while routing the request to a weaker model. On easy tasks, you may not notice. On hard tasks, the output feels slightly dumb.
You blame the model. Maybe the model never answered.
Why coding agents make this worse
This was less dangerous when AI was only a chat box. You typed a question. It answered.
Now coding agents work inside projects. They read files, run commands, inspect errors, and produce patches. They may send a large part of your working context to the model.
That is why cheap proxy risk is different from normal AI privacy risk.
With an agent, the prompt is not the whole leak. The workspace is the leak.
If you route that through an unknown proxy, you are trusting a stranger with the shape of your project.
The safe rule
Do not use unofficial AI proxies for private work.
Use them like a public pastebin.
Safe enough:
public examples
throwaway prompts
learning experiments
Do not send:
client code
private repositories
API keys
product plans
customer data
internal docs
agentic coding sessions
For serious work, use an official API, a trusted aggregator with clear data terms, a paid subscription, or a lower-cost model from a legitimate route. The cheap path is fine only when the work is already disposable.
Now go and build something great
The ShortList
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