Token Factory Monetization Channel Map: From Aggregation Platforms to Direct Wholesale

Introduction: The Channel Dilemma of Token Monetization

When compute clusters process tokens at millions of IOPS throughput, a practical question emerges: how can these tokens be converted into sustainable revenue? The marginal cost of large model inference is rapidly declining, but downstream demand—from AI applications and agents to video generation—varies widely in willingness to pay and ability to pay. The choice for compute suppliers is not "whether to sell," but "to whom and how to sell."

Currently, the market has three main monetization channels: aggregation platforms (e.g., API marketplaces), direct enterprise customers (private deployment), and industry wholesale, which sits between the two. Each channel differs in payment terms, pricing power, and scale ceiling. This article aims to draw an actionable channel map for token factories, helping decision-makers choose the optimal path based on their resource endowments.

Aggregation Platforms: Balancing Traffic Entry and Pricing Power

Aggregation platforms (e.g., model inference APIs on major cloud marketplaces) are the "fast lane" for token monetization. Suppliers package compute resources into standard APIs, and once connected to the platform, they can reach thousands of small and medium-sized developers. The advantage of this channel lies in stable traffic and low technical integration costs—platforms typically provide unified authentication, billing, and monitoring systems.

However, pricing power on aggregation platforms is highly centralized. Supplier quotes must align with the platform's pricing strategy, and profit margins are often compressed to the 10–20% range. For example, on one major platform, the API price is approximately ¥0.15 per thousand tokens, with the supplier's actual share around ¥0.12 per thousand tokens. For hardware like the FX100, with a reference price of approximately ¥371,200 (about ¥2,014/TB) [vendor specification], if a single machine achieves a throughput of 74.9 tok/s (measured, report R2), the theoretical daily revenue is about ¥7,800. After deducting electricity, maintenance, and platform fees, net profit margins are limited.

A more critical constraint is that aggregation platforms require standardized interfaces, meaning suppliers cannot perform differentiated optimizations for specific scenarios (e.g., KV cache reuse for agents, continuous inference for video generation). For suppliers seeking high-value-added services, aggregation platforms are better suited as "traffic testing grounds" rather than primary battlegrounds.

Direct Wholesale: Structural Opportunities in Private Deployment

Direct enterprise customers represent the "profit high ground" for token monetization. Typical scenarios include risk model inference for financial institutions, diagnostic imaging agents for healthcare, and cloud inference clusters for video generation platforms. These customers have rigid requirements for data privacy, latency stability, and customized services, and are willing to pay a premium for private deployment.

Take a typical private deployment contract as an example: the customer purchases an FX100 all-flash NVMe-oF array (4-disk RAID0, 14 TB, RoCEv2, single-port 100 GbE) [test platform description, reports R1–R4], paired with compute servers. The contract value typically ranges from ¥2 million to ¥5 million, including hardware, deployment, and three years of maintenance. The gross margin for such contracts can reach 40–60%, far exceeding that of aggregation platforms.

However, direct wholesale has its barriers. The customer decision-making chain is long, typically requiring 3–6 months from technical validation to contract signing. Additionally, customers impose strict performance verification requirements—for example, Mingxin's joint testing model includes approximately 10 weeks of gated testing (G1: arrival acceptance, G2: single-machine baseline, G3: main gate: TTFT reduction ≥25%, throughput +29–40% measured in-band, G4: 72-hour stability) [cooperation model], with termination if targets are not met. While this "measured in-band" commitment reduces customer risk, it also demands solid delivery capabilities from suppliers.

For emerging scenarios like agents and video generation, the premium for private deployment is even greater. Agent inference workloads are highly bursty (e.g., frequent KV cache reads/writes in multi-turn conversations), while video generation imposes stringent requirements on continuous inference throughput. Suppliers that can perform joint software-hardware optimization for these scenarios (e.g., LMCache parallel read patch improving TTFT by 4.1×, measured, report R1) will gain stronger bargaining power.

Industry Wholesale: An Intermediate State Between the Two

Industry wholesale channels serve as a transitional form between aggregation platforms and direct wholesale. Suppliers sell compute resources in the form of "machine time packages" or "token packages" to industry intermediaries (e.g., AI application developers, MCN agencies), who then repackage them for end users.

The advantages of this model include short payment terms (typically monthly settlement), a manageable number of customers (dozens rather than thousands), and partial retention of pricing power by the supplier. For example, in the video generation scenario, an MCN agency might require 5 million tokens of inference capacity per month. The wholesale unit price can be negotiated to ¥0.08–0.10 per thousand tokens, lower than the aggregation platform split but higher than the direct wholesale price, and without the need to bear end-user maintenance costs.

The risk of industry wholesale lies in the creditworthiness of intermediaries. Industry data from 2025 shows that approximately 15% of intermediaries face overdue payments or default risks. Therefore, suppliers need to establish credit evaluation mechanisms, such as requiring advance payments or adopting a "payment first, volume later" model. For high-end equipment like the FX300, with a reference price of ¥924,000 (about ¥5,014/TB) [vendor specification], a single unit can support dozens of intermediaries, but cash flow recovery must align with hardware depreciation cycles.

Decision Framework for Channel Selection

There is no single "optimal channel"; only combination strategies suited to specific stages. The following framework can serve as a reference:

• Startup Phase (1–2 years): Prioritize connecting to 2–3 aggregation platforms to validate market willingness to pay for tokens, while accumulating performance data (e.g., TTFT reduction of 26–32%, measured, report R2). The goal at this stage is not profit maximization, but gaining customer feedback and reputation.
• Growth Phase (3–5 years): Shift toward industry wholesale, establishing long-term partnerships with 5–10 intermediaries. Simultaneously, develop differentiated services for agent and video generation scenarios (e.g., KV cache tiered acceleration improving inference throughput by 29–40%, measured, reports R2/R3), building technical reserves for direct wholesale customers.
• Maturity Phase (5+ years): Make direct wholesale the primary channel, targeting leading enterprises in finance, healthcare, and video generation. Aggregation platforms and industry wholesale serve as traffic supplements and cash flow buffers.

Conclusion: The Last Mile from Tokens to Revenue

The monetization of token factories essentially involves converting compute power into quantifiable customer value. Aggregation platforms provide traffic, direct wholesale provides profit, and industry wholesale provides flexibility. For compute suppliers, the key is not to choose a single channel, but to establish a "channel portfolio" strategy, dynamically adjusting weights based on market changes.

Mingxin Technology focuses on storage acceleration and domestic computing, with verified results in KV cache optimization and model loading acceleration (6.2–9.3× improvement vs. NFS, measured, report R9). Teams interested in private deployment or joint testing are welcome to contact us through official channels to explore more possibilities for token monetization.