What happens when the world’s most valuable chip maker starts acting like a venture capitalist? For Web3 builders, it’s both a lifeline and a trap.
From the ashes of 2022, we planted seeds for 2030. That was our mantra during the bear market—a quiet promise to build infrastructure that would outlast the hype. Now, a new kind of infrastructure deal is emerging, and it isn't coming from a DAO or a protocol. It's coming from Nvidia.
In 2024, Nvidia quietly launched a revenue-sharing program that lets AI startups access its top-tier GPUs—like the Grace Blackwell GB300—without paying upfront. Instead, these startups agree to share a percentage of their future revenue with Nvidia. At first glance, this seems like a benevolent move: democratizing compute for cash-strapped innovators. But as a Web3 community founder who has watched the lines between AI and crypto blur over the past three years, I see something more sinister—and more fascinating.
This is not just a sales tactic. It is a financial instrument designed to lock the next generation of AI-native companies into Nvidia’s ecosystem, using the very same capital mechanisms that DeFi was meant to disrupt.
Context: The Plan and Its Players
The mechanics are straightforward. Instead of buying GPUs or renting them from hyperscalers like AWS or Google Cloud, startups can apply to Nvidia's revenue-sharing program. Nvidia evaluates their potential—often through partners like CoreWeave, in which it holds a 7% stake—and then deploys hardware into datacenters operated by companies like Firmus (building a 360MW, 170,000-GPU site in Indonesia) or Sharon AI (installing 40,000 GB300 chips for “sovereign compute” outside the U.S.). In return, Nvidia takes a cut of the startup’s future top line.
Nvidia’s CFO has called this a shift from “one-time payments” to “recurring, usage-based revenue streams.” It’s a classic SaaS play, but dressed in hardware and backed by the world’s most valuable semiconductor company. And it comes at a time when big customers like Meta and Microsoft are cutting orders and building their own chips.
Core: The Technical and Values Analysis
Let me be clear: I am not criticizing innovation in business models. What concerns me is the lock-in effect that this plan creates—not just commercially, but technically.
Every startup that signs up for this program commits to “multi-year binding to Nvidia chips and software.” That means their codebases, optimization routines, and even their model architectures will be tuned to CUDA—Nvidia’s proprietary software layer. Migrating to AMD’s ROCm or Intel’s OneAPI later would require rewriting years of work. This is the old vendor lock-in trick, now amplified by AI’s insatiable hunger for parallelism.
But here’s where the Web3 lens sharpens the picture. We have spent a decade building systems that resist central points of control—decentralized blockchains, open-source protocols, permissionless access to capital. Yet the compute layer that powers the most transformative technology of our time is being financially engineered into a walled garden.
Think of it this way: in DeFi, we use liquidity pools to ensure no single entity controls the terms of a swap. Nvidia is building a liquidity pool for compute, but the pool is closed, the prices are opaque, and the terms are dictated by a single counterparty. If you are an AI startup building on decentralized infrastructure—say, a crypto-native AI agent that needs on-chain inference—you have just handed Nvidia a percentage of your token revenue forever.
This isn’t just a business model; it’s a new form of conditional ownership. It mirrors the “revenue-based financing” that DeFi protocols like Maple Finance pioneered for lending. But where Maple uses smart contracts and transparent risk parameters, Nvidia’s program relies on private negotiation and corporate discretion. The irony is thick: the hardware that enables decentralized intelligence is being distributed through a centralized credit desk.
The Hidden Mechanics: Technology Lock-In and Capital Reallocation
From my own experience auditing DeFi protocols, I’ve seen how arbitrary interest rate models can warp an entire ecosystem. Compound’s rates have little to do with real supply and demand—they’re set by parameters chosen in a governance vote. Similarly, Nvidia’s revenue-sharing percentages are undisclosed. We don’t know what cut they demand, or how they assess credit risk. That lack of transparency is dangerous.
Consider the hidden costs. First, the plan is effectively a high-interest loan denominated in GPU compute. For a startup with a high failure rate (as most AI startups are), the effective interest rate could be astronomical. Second, Nvidia is using this program to hedge its own capital expenditure risk. Big customers are cutting orders, but Nvidia has built massive wafer capacity. By converting future GPU supply into long-term receivables from startups, Nvidia is smoothing its own revenue at the expense of startup balance sheets.
Third—and this is critical for the crypto community—the program accelerates the “compute as capital” trend. We already see this in crypto mining, where miners finance GPU purchases through future block rewards. Nvidia is now doing the same, but with AI compute. The result is a reallocation of risk: the hardware supplier becomes the financier, and the innovator become the debtor. This is the opposite of the disintermediation that blockchain promises.
From an infrastructure perspective, the plan is already triggering massive buildouts. Firmus’s 360MW site in Indonesia will require enormous power and cooling. Sharon AI’s “sovereign compute” outside the U.S. hints at geopolitical spillover. Crypto-native compute networks like Render Network or Akash Network must now compete with a supplier that can provide hardware at below-market upfront costs—but only if the user surrenders future revenue. The global map of AI compute is being redrawn around Nvidia’s financial footprint.
Contrarian: The Counter-Intuitive Angle
But let me play devil’s advocate against my own instinct. Perhaps this plan is exactly what small Web3-native AI projects need. Right now, most decentralized compute marketplaces suffer from low liquidity and high latency. They cannot match the performance of a dedicated GB300 cluster. Nvidia’s program could give a promising AI-dAO access to world-class hardware without diluting its token supply through a traditional VC raise. The revenue share becomes a kind of “compute bond” that aligns Nvidia’s interests with the startup’s success.
And there’s a historical parallel here. In the early days of the internet, Cisco and Oracle provided supplier financing to young companies. That fuel helped build the dot-com infrastructure. Some of those companies became the giants of today. Similarly, Nvidia’s program might be the capital injection that allows AI-crypto hybrids to finally reach production scale.
But here’s the catch: the dot-com era also ended with massive defaults when the funded companies failed. Michael Burry, of all people, has warned that Nvidia’s plan resembles the “cyclical financing” that inflated the housing bubble. If a wave of AI startups defaults on their revenue commitments, Nvidia’s balance sheet could be hit hard. And because the program is opaque, the true scale of this risk is hidden.
For the crypto world, the contrarian take is this: Nvidia’s program might actually be a Trojan horse that forces decentralization. If enough startups become dependent on Nvidia and then find the terms suffocating, they might have a strong incentive to switch to open-source hardware initiatives or decentralized compute networks. The lock-in could breed a counter-movement. The same way that AWS monopoly spawned multi-cloud architecture, Nvidia’s financial grip could accelerate the adoption of fully permissionless compute layers.
Takeaway: The Future is a Shared Ledger of Compute
Trust is built in the bear, sold in the bull. As the AI-crypto cycle heats up, the tools we use to build must be scrutinized not just for performance, but for the power structures they encode.
Nvidia’s revenue-sharing plan is a brilliant financial innovation—but it is also a warning. It reminds us that the real battle in AI infrastructure is not just over teraflops, but over the terms of access. In Web3, we have spent years fighting for open financial rails. Now we must fight for open compute rails, too.
Resilience is the new utility. The question is: will we build our own liquidity pools for compute, or will we accept the ones handed to us by a single chipmaker?
From the ashes of 2022, we planted seeds for 2030. Those seeds were supposed to grow into a forest of decentralized infrastructure. But if the soil is controlled by one company’s financial instruments, the forest may never be more than a monoculture.
Visionaries plant trees they never sit under. Nvidia is planting trees and charging rent for the shade. The Web3 community must plant its own orchard.