A multi-year compute contract can create a financing problem months before the first GPU is used.

A buyer may reserve future capacity with a deposit or prepayment due when the contract is signed, while the underlying cluster is still weeks or months away from being ready for service. The provider gets the commercial commitment it needs, but the buyer has to decide how much cash it wants tied up before the infrastructure is usable.

For a growing AI company, the question is therefore not only how much compute to buy. It is also:

How much cash should we commit before the capacity is available, and when does financing that prepayment make more sense?

This guide explains how compute prepayments work, why companies finance them, how lenders assess younger AI companies and what buyers should check before signing a compute contract.

What this guide covers: financing compute purchases, meaning what an AI company pays a provider for capacity. It does not cover financing data center builds or a provider's own GPU fleet.

Key terms

How do AI companies buy compute?

AI companies can buy compute on demand or commit to capacity for a defined period. Committing to future capacity can mean paying a meaningful amount before the GPUs are ready.

On-demand compute provides flexibility. The buyer consumes capacity as needed and pays based on usage.

Reserved or committed capacity gives the buyer access to compute for an agreed period. It can provide greater certainty around availability and commercial terms, but it also creates a larger financial commitment.

For future capacity, the provider may require a deposit or prepayment before the GPUs are ready for service. That creates a timeline that can look like this:

Contract signed → prepayment due → deployment period → ready for service (RFS) → compute becomes usable

The financing question sits in the gap between the upfront payment and RFS.

How much is due up front?

There is no single standard. The amount depends on the provider, the capacity and the contract structure.

In recent Gynger conversations and program designs, upfront requirements have ranged from roughly 10% to 35% of total contract value, with some proposed structures going higher. New-generation clusters that are still several months from delivery tend to create the clearest prepayment problem. Shorter-term or already-available capacity may require a smaller upfront commitment.

These figures are examples from current transactions and discussions, not a market-wide benchmark.

Recent conversations on both sides of the market point to the same issue. One AI compute buyer described prepayment as the biggest bottleneck in securing additional capacity. One provider described customers who were reluctant to fund deposits several months before the underlying clusters would be available.

That is why Gynger's current compute focus is primarily on deposit and prepayment financing rather than financing the entire value of a multi-year compute contract.

Why does financing come up before the compute does?

Because cash can leave the business long before the compute starts creating value.

Imagine an AI company secures a GPU cluster that will be ready in five months. The provider requires a meaningful part of the contract value up front.

If the buyer pays from cash, that capital leaves the business today even though the GPUs cannot yet be used.

For an early-stage or growth-stage company, the opportunity cost can be significant. The same capital could remain available for product development, hiring, sales or other operating needs.

Cash position and runway are particularly important for venture-backed companies. Tying up a large amount of cash in compute before delivery can put additional pressure on liquidity even when the company technically has enough money to make the payment.

There is also a second issue: delivery risk.

The buyer is committing capital today against infrastructure expected to arrive later. Providers and buyers alike have described concern about paying months ahead of delivery when a cluster can still be delayed or fail to arrive as expected.

Financing the prepayment does not change when the cluster arrives. It can, however, change how much of the buyer's own capital is tied up before delivery, and, depending on the financing terms, what the buyer owes if the capacity never arrives.

So the question is broader than can we afford the deposit? It is also: do we want this much cash tied up before the compute is usable?

What is prepayment financing?

Prepayment financing covers an eligible deposit or upfront payment required as part of a compute purchase. The buyer and provider still agree on the commercial transaction, and the financing sits alongside it.

A typical structure looks like this:

1. The buyer agrees to purchase or reserve compute from a provider.

2. The provider requires a deposit or prepayment before the capacity is available.

3. The buyer applies for financing for that upfront requirement.

4. The lender underwrites both the buyer and the underlying transaction.

5. The provider receives the financed amount up front.

6. The buyer repays according to the agreed financing terms.

The underlying compute contract remains between the buyer and provider. The financing agreement is separate.

How long is the financing?

Prepayment financing is designed around the period between the upfront payment and delivery.

For Gynger's current compute program, that generally means short-duration financing of up to six months, aligned to the expected RFS date. Depending on the structure, repayment can be made in installments or as a single payment under the agreed terms.

Is the whole compute contract being financed?

Not necessarily.

A company can sign a large multi-year compute contract but only finance the upfront deposit. In that case, the lender is underwriting the amount it is actually financing rather than automatically financing the entire TCV.

That distinction matters. A large contract can create a much smaller, shorter-duration financing need at the start of the transaction. It also shapes the cost: because the financing applies only to the deposit, and only until RFS, it can be a small fraction of the contract's total value.

Worked example: a large contract with a short financing need

Illustrative only. Not a quote, financing offer or description of standard terms.

An AI company signs a three-year compute contract with a total contract value of $10 million. The provider requires a 20% deposit, and the cluster is expected to be ready for service in four months.

The commercial commitment is $10 million, but the immediate financing need is $2 million.

The compute purchase itself has not changed. What changes is when the buyer has to use its own capital.

Why finance a prepayment if the company already has the cash?

Because liquidity has a value of its own.

For an early-stage AI company, much of the cash on the balance sheet may have come from an equity raise. That capital is also funding the product, the team and the growth of the business. Using a substantial portion of it for a compute prepayment can reduce runway months before the corresponding infrastructure is usable.

For a growth-stage company, the numbers become larger but the trade-off remains similar. Compute may be essential to the business while capital is also needed for hiring, product development and customer acquisition.

A larger cash-generative company may make a different decision. If the upfront requirement is small relative to available liquidity, paying directly can be perfectly rational.

The relevant comparison is therefore between the cost of financing and the value of keeping that cash available elsewhere in the business.

Financing becomes particularly relevant when:

• the prepayment is material relative to available cash

• the payment is due well ahead of delivery

• preserving runway is strategically important

• the company has higher-value uses for that capital while it waits for RFS

What can go wrong between prepayment and delivery?

Three things matter most: the capacity is not delivered, it arrives late, or the buyer cannot meet its financing obligations.

The capacity is not delivered. A provider may commit to future capacity and later fail to deliver it. Compute infrastructure depends on more than the GPU itself. Hardware availability, power, data center readiness and deployment constraints can all affect whether a cluster becomes available as expected.

The capacity arrives late. The GPUs eventually become available, but later than the contracted date. Even if the buyer ultimately receives the compute, a delay can be commercially significant if model training, inference capacity or a customer launch depends on it.

The buyer cannot meet its financing obligations. The provider delivers the agreed capacity, but the buyer cannot make the required payments under the financing agreement.

This is why a compute financing structure has to distinguish between delivery risk and buyer credit risk.

In Gynger's current deposit-financing model, the provider remains responsible for delivery under the compute contract, while Gynger underwrites the buyer credit exposure on the financed amount, subject to the agreed financing and program terms.

Financing doesn't change whether or when the provider delivers. The underlying compute contract still needs to spell out what happens if the provider delivers late or not at all. 

How do lenders underwrite a young AI company?

By looking at both the company and the compute transaction.

Many AI companies buying significant amounts of compute are young and venture-backed. They may not have years of historical revenue or profitability, so underwriting cannot rely only on backward-looking financials.

Providers tend to see buyers on a ladder: investment-grade companies at the top, then unrated public companies, then the largest AI labs, with inference providers and younger AI companies below. The further down that ladder a buyer sits, the less a provider can rely on reputation alone, and the more the underwriting has to do.

The company review can include:

• Business model: what the company does and how central compute is to its product or revenue

• Revenue and growth: historical revenue where available and how the business is developing

• Contracted revenue: executed customer agreements that provide evidence of future revenue

• Cash position and burn: how much liquidity the company has and how quickly it is using it

• Runway: how long the company can operate at its current burn and how the proposed financing affects that runway

For earlier-stage venture-backed companies with limited history, Nancy Jain, Director of Credit at Gynger, points to cash, runway, investor backing and contracted revenue as what matters most.

The transaction review can include:

• the compute provider and the operator's delivery track record

• the GPU type and quantity

• the contract price compared with market benchmarks and price indices

• the deposit amount and refund terms if capacity isn't delivered

• the expected delivery or RFS date

• the term and payment structure of the compute commitment

• the resale options for the capacity and the likely recovery compared with the contract price

This matters because a lender is not only asking whether the company can repay. It is also assessing the transaction the financing is attached to.

Underwriting also does not have to result in a simple yes or no. A lender can approve a smaller amount than requested if that better matches the buyer's financial profile and the risk of the transaction.

What should you check before signing a compute contract?

The headline price per GPU-hour is only one part of the economics.

Before making a significant commitment, buyers should understand:

• When will the capacity actually be ready? A strong price is less useful if the compute arrives too late for the workload it was purchased for.

• How much is due before delivery? The size of the prepayment and the time between payment and RFS determine how much capital is committed before the compute becomes usable.

• What happens if delivery is delayed? The contract should explain what happens if the agreed readiness date slips.

• What happens if the capacity is never delivered? Buyers should understand their contractual protections before committing capital.

• Who is actually delivering the compute? The seller, marketplace, broker and underlying operator are not always the same party. Understand who ultimately controls the infrastructure and is responsible for delivery.

• What are the minimum commitments? A lower unit price may come with a larger or longer obligation.

• Can the commitment be transferred or assigned? This may matter if the buyer's infrastructure needs change.

• How does the payment schedule work after RFS? The deposit may only be one part of the cash commitment.

• How could the economics change during the contract? GPU pricing, available generations and the buyer's own infrastructure needs can all evolve during a long commitment.

Why is future compute particularly difficult to buy?

Because the provider wants to secure the customer early, while the buyer would prefer to commit cash closer to the point when the capacity is usable.

The economic value of the capacity can also change as the delivery date approaches. Providers have described immediately available compute as easier to sell than otherwise similar capacity that is still months away, because buyers often need GPUs as soon as possible.

That creates a structural timing mismatch. The provider wants an early financial commitment against future capacity. The buyer wants to avoid tying up a large amount of cash before that capacity is usable.

Prepayment financing sits directly between those two incentives. The provider can receive the upfront payment required by the transaction, while the buyer preserves more of its own capital during the period before RFS.

Where does Gynger fit?

Gynger provides financing infrastructure for compute, with a current focus on deposits and prepayments.

For eligible transactions, Gynger reviews both the buyer and the underlying compute purchase, determines an appropriate financing amount and funds the eligible upfront requirement.

The typical structure is straightforward:

Buyer signs with provider → Gynger underwrites → Gynger funds the eligible prepayment → provider delivers → buyer repays Gynger

The underlying compute contract remains between the buyer and provider. Gynger lends directly to the buyer and manages the financing relationship.

A buyer can also bring Gynger a compute transaction when Gynger does not already have a relationship with the provider. Gynger can review the buyer and transaction and, if approved, fund the provider directly.

For providers, the same financing infrastructure can also be offered through a co-branded or embedded flow, allowing customers to apply for payment terms as part of the buying process.

Buying compute and facing a deposit or prepayment? Start the process to get approved →

The takeaway

The financing problem in compute often starts long before the first GPU is used.

A company agrees to secure future capacity. A provider requires money up front. The GPUs may only become available months later.

During that period, the buyer has to decide how much capital it wants tied up, what delivery risk it is taking and whether paying the full upfront requirement from cash is the best use of its liquidity. For many growing AI companies, that makes the deposit itself the most immediate financing problem.

Before signing a large compute commitment, understand how much is due up front and how long until the capacity is usable, who is responsible for delivering it and what happens if delivery fails, and whether cash is the best use of the company's capital while it waits.

Those questions can matter just as much as the price per GPU-hour.

Frequently asked questions

How much is a deposit on GPU compute? It varies by provider and transaction. In recent Gynger conversations and program designs, upfront requirements have ranged from roughly 10% to 35% of contract value, with some proposed structures going higher. These examples should not be treated as a market-wide benchmark.

Can you finance a GPU deposit or prepayment? Yes. Prepayment financing can cover an eligible deposit or upfront payment so the provider is paid while the buyer preserves more of its own cash during the period before the capacity is ready.

How long does prepayment financing last? The financing is generally designed around the period between the upfront payment and RFS. For Gynger's current compute program, that is typically up to six months. The exact term is set as part of underwriting and the transaction structure.

Does the buyer have to repay monthly? Not necessarily. Depending on the structure, repayment may be made in installments or as a single payment under the agreed terms.

Is it expensive to finance a compute deposit? It depends on the buyer and the transaction. Because the financing covers only the deposit, and only until the capacity is ready, the cost can be a small fraction of the contract's total value.

Is it better to pay cash or finance a compute deposit? It depends on the company. Early-stage and growth-stage companies may place a high value on preserving cash for product, hiring and operations. A cash-generative company with a relatively small upfront requirement may reasonably choose to pay directly.

How do lenders evaluate AI startups for compute financing? They can look at the business model, revenue or contracted revenue, cash position, burn and runway, as well as the underlying compute transaction, including the provider, deposit, capacity and expected delivery date.

Does prepayment financing remove delivery risk? It doesn't remove the operational risk: if a cluster is late, the compute is still late, and buyers should understand the delay and non-delivery provisions in the compute contract. Whether you still owe the financing if capacity is never delivered depends on the financing terms. 

Do I need a provider that already works with Gynger? No. A buyer can bring Gynger an eligible compute transaction even if Gynger does not already have a relationship with the provider.

Does Gynger finance the entire compute contract? Gynger's current compute focus is on deposits and prepayments. In many transactions, the financing need is only the upfront portion of a much larger compute contract.

Last updated: November 2026 · With input from Nancy Jain (Director, Credit), and Gynger's product and go-to-market teams.