卖 AI token 越来越难:折扣转售生意正在瓦解
Selling AI Tokens Gets Harder as the Discount Trade Unravels
- 1AI 订阅与 token 充值在中国购物季摆上普通电商货架,用量消费品化让稀缺型中介生意松动
- 2转售行业分三层,聚合平台、推理服务商与小型 API 店,折扣既是卖点也是风险来源
- 3头部推理服务商日 token 量达数千亿并递表港股,公开账目显示负毛利与大幅净亏损
- 4模型调包疑虑、大实验室半年封禁数百万账户、监管责令整改,灰色折扣生意正在收紧
token 转售差价生意的前提正在消失,供给不再稀缺后中介价值转向合规、可计量与配套服务。
- 影响:低价第三方渠道伴随模型调包与上游封号风险,非官方接口审计显示性能差距明显;采购评判正从单价转向单位付费的实际产出与合规资质;走向正规授权的渠道价格将高于灰市。
- 参考:可考虑对在用的第三方 API 供应商做模型身份抽测并留存比价记录;值得把官方货架、运营商套餐与企业平台报价放进同一预算口径比较,再评估在代码等场景引入自动路由降本。
- 依据:依据包括大实验室披露的半年数百万封禁账户数据、网信监管整改通报,以及安全研究者对非官方接口的审计结果,OpenRouter 经济性为媒体报道口径。
NextFin News — Artificial-intelligence usage is starting to look like a consumer product. During China’s peak shopping season, cloud companies and model labs have been placing subscriptions and token top-ups on ordinary e-commerce shelves, sometimes discussing bundles aimed at students, families, and solo operators. The pitch is simple: pay for intelligence the way people once paid for mobile data. Demand is real enough to support that experiment. The middlemen who grew up when access was scarce are learning that scarcity is no longer the whole business.
Three layers, three economics
Between a model weight and a finished answer sits a messy industry that is often labeled, too loosely, as “transit.”
At one end are aggregation platforms that expose hundreds of models through a single developer surface. Their pitch is choice under constraint: match a job to capability, latency, price, and uptime without maintaining a separate integration for every lab. When Stripe moved to acquire OpenRouter, public discussion focused less on retail markup than on that routing layer—and on reported economics far richer than a pure pass-through would suggest.
Closer to infrastructure sit Chinese inference specialists that sell metered access alongside dedicated capacity, acceleration, and private deployment, including the ability to run models across different chip vendors. User and throughput figures published for leaders in this group run to large consumer registration bases, substantial enterprise rosters, and daily token volumes in the hundreds of billions. Several rounds of funding and a Hong Kong listing application signal that investors treat the category as real infrastructure. The same public accounts also show how hard the math can be: a year of rapid volume with negative gross margin and a wide net loss is a reminder that tokens are not a free cash machine.
Below both sits a long tail of small API shops. They advertise unified endpoints, prepaid balances, and list prices that can look like a fraction of official rates for premium foreign models. Comparison blogs and mini-sites help buyers sort quotes and top-up friction. Some offers blur into account trading—bundled logins and subscription entitlements sold by the month, with weak promises after the upstream vendor bans the credential. Ban statistics disclosed by major labs run into the millions of accounts over half-year windows; only a slice of appeals succeed. Convenience and fragility often share the same storefront.
The discount is the product—and the risk
Users already assume that extreme markdowns are not charity. Bulk purchase, promotional quotas, and splitting a single subscription across many callers are among the cleaner explanations operators give. The darker worry is substitution: the name on the catalog need not be the model that returns the tokens. Security researchers auditing unofficial “shadow” endpoints have reported large gaps versus official performance and frequent failures on model-identity tests. Buyers trade detection prompts, third-party scoreboards, and war stories of refunds that end in deleted accounts.
Authorities have begun treating the pattern as more than a consumer nuisance. Enforcement summaries from cyberspace regulators have cited websites that relayed multiple large-model interfaces without required assessments and with content-safety failures, ordering corrections and warning responsible individuals. Domestic models are not exempt from dilution complaints; at the same time, open aggregation dashboards have shown Chinese systems taking a majority share of global token consumption in recent weeks. Popularity widens the market for intermediaries. It does not automatically widen honest margin.
Where a middle layer still earns its keep
After closures and scrutiny, some shops try to reappear under formal authorization. Licensed supply, compliance overhead, and support cost more; prices stop resembling the gray market. That may be the point. Another path is to stop leading with the meter. Cloud groups can sell invocation inside a bundle of compute, storage, security, and application plumbing—procurement criteria that unit price alone does not win. Telecom operators have started wrapping token allowances into plan-like products, searchable inside carrier apps in national or provincial pilots. Habit formation, not announcement, will decide whether those packs become as ordinary as data refills.
A third path treats intelligence as the product and tokens as the fuel. Automatic routing that picks cheaper or smaller models when the task allows can cut spending sharply in coding and mixed workloads when evaluations hold up. The competitive question becomes how much useful work each paid unit performs, not how loudly the storefront advertises a discount.
Model use is still rising. Official shelves, operator packs, and enterprise platforms are normalizing payment. Arbitrage that depended on opaque upstream supply and hopeful buyers is a worse trade than it was when alternatives were thin. The intermediaries that endure will look less like outlet stores for someone else’s API and more like controlled pipes—measurable, accountable, and paid for a service that survives a price comparison.



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