On March 19, 2026, ZhenFund, together with “Crossing” (十字路口 Crossing), launched a program called Token Grant, offering 50,000 RMB of token and compute support per project to founders who have already built a first version of an AI product and are in the early exploration stage.

1. Core Details of the Program

According to the official announcement, Token Grant is positioned as non-dilutive early-stage resource support, not equity investment. Its key terms can be summarized as follows:

In its FAQ, the official announcement stresses that the program is not a fundraising gate test, nor an early judgment of whether a founder is “qualified to raise”. Teams that have already raised funds can also apply, but priority goes to founders and super individuals who have not yet completed institutional fundraising and are still in the early product-exploration stage.

2. Analysis of the Positive Value

1. Non-dilutive funding support lowers early trial-and-error costs

For solo developers or 1–3 person teams, 50K RMB isn’t a huge amount, but as “fuel money” that requires no equity, it can directly cover the compute costs of multiple rounds of model calls, agent-architecture validation, and inference testing, easing early-stage financial pressure.

2. The brand-backing value may outweigh the cash itself

As a top-tier early-stage investor in China, ZhenFund’s brand label itself carries a screening and trust-endorsement effect. Selected projects not only receive token credits but also enter ZhenFund’s observation network, gaining direct access to investment partners like Koji. This kind of ecosystem access has potential leverage for future fundraising, hiring, and industry exposure.

3. The entry threshold is designed to be friendly

Terms like “you don’t need to be a company” and “no model vendor lock-in” clearly lower the participation barrier for non-technical founders and independent developers (super individuals). This aligns with the “one-person company” narrative in the current AI agent startup wave.

4. A signal to the industry

Shipping “Token Grant” as a standalone product is ZhenFund’s public bet on the AI-native application / agent track. Programs like this often trigger copycats from other institutions, making it a bellwether for the industry.

3. Limitations and Hidden Costs

1. The real compute ceiling of 50K RMB is limited

If a project involves multi-agent collaboration, high-frequency LLM calls, or deep reasoning models (e.g., o1, Claude Opus), 50K RMB can burn through quickly at the scaling-test stage. This money is better suited to the validation phase; it’s hard for it to sustain the ongoing compute needs of a growth-stage product.

2. Time cost and attention fragmentation

The investment team’s “full participation” means selected founders must spend time on regular updates, demo presentations, and absorbing feedback. For early teams pursuing extreme leanness, the time cost of communicating with investors may offset part of the value of the funding support.

3. It’s still a screening funnel at heart

Despite the official statement that it’s “not an investment judgment,” a grant program run by an investment institution is fundamentally still an upstream talent and project screening mechanism. Selected projects enter ZhenFund’s investment radar with a higher chance of follow-on funding — but that also means bringing a specific capital’s evaluation perspective in from the early stage.

4. Competition is fierce; opportunity cost is real

Grant programs at top funds typically attract huge application volumes for limited slots. Applicants need to weigh whether the time and effort spent preparing application materials is worth the expected return.

4. Who It Fits

Good candidates:

• Have a first version of an AI product (MVP) and are rapidly iterating and testing
• Have not yet completed institutional fundraising, or are solo developers / 1–3 person teams
• Need compute support and also value an investor’s brand endorsement and network resources

Limited value for:

• Founders still at the pure-idea stage with no usable product
• Teams that have completed Series A or later and have relatively ample compute budgets
• Builders who want to stay fully independent and avoid exposure to capital’s perspective too early

5. Summary

The greatest value of ZhenFund’s Token Grant may not be the 50,000 RMB itself, but the combined payoff of “non-dilutive funding + top-tier institutional endorsement + early investor relationships.” For AI founders and super individuals in the product-validation stage with tight resources, this is an opportunity with relatively controllable costs and potential upside worth trying.

But it also deserves rational assessment: the grant’s compute support has its ceiling, and participation requires time and attention. Treating it as an accelerator that lowers early trial-and-error costs, rather than a replacement for long-term operating capital, is probably the more pragmatic expectation.