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Axe Compute Inc. (the “Company”) is filing this Current Report
on Form 8-K to disclose updated risk factors relating to the Company’s expansion into the purchase, ownership, and operation of
GPU computing infrastructure deployed in data center facilities. The updated risk factors supplement and update the risk factors disclosed
in Part I, Item 1A of the Company’s Annual Report on Form 10-K for the fiscal year ended December 31, 2025 (the “2025 Form
10-K”).
The updated risk factors are set forth in Exhibit 99.1 attached hereto and
are incorporated herein by reference. These risk factors should be read together with the risk factors and other information contained
in the 2025 Form 10-K and the Company’s subsequent filings with the U.S. Securities and Exchange Commission. To the extent the risk
factors set forth in Exhibit 99.1 are inconsistent with the risk factors in the 2025 Form 10-K, the risk factors in Exhibit 99.1 supersede
those risk factors.
The information set forth in this Item 8.01, including Exhibit 99.1, is being
“filed” for purposes of Section 18 of the Securities Exchange Act of 1934, as amended, and is hereby incorporated by reference
into any filing made by the Company under the Securities Act of 1933, as amended, or the Exchange Act, to the extent not superseded by
information contained therein.
Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused
this report to be signed on its behalf by the undersigned hereunto duly authorized.
EXHIBIT 99.1
RISK FACTORS
The following risk factors supplement and update the risk factors disclosed in Part I, Item
1A of the Annual Report on Form 10-K of Axe Compute Inc. (the "Company," "we," "us," or "our")
for the fiscal year ended December 31, 2025 (the "2025 Form 10-K"), and reflect the Company's expansion into the purchase, ownership,
and operation of GPU computing infrastructure deployed in data center facilities. These risk factors should be read together with the
risk factors and other information contained in the 2025 Form 10-K and our subsequent filings with the U.S. Securities and Exchange Commission.
To the extent the following is inconsistent with the risk factors in the 2025 Form 10-K, the following supersedes those risk factors.
Any of the following risks could materially and adversely affect our business, financial condition, results of operations, and prospects,
and the trading price of our common stock could decline. Additional risks and uncertainties not currently known to us or that we currently
deem immaterial may also impair our business operations.
Risks Related to Our Ownership and Operation of GPU Computing Infrastructure
Our expansion into owning and operating GPU computing infrastructure is capital-intensive
and will require substantial and growing capital expenditures, and any inability to obtain capital on acceptable terms may adversely affect
our business.
We have historically pursued an asset-light operating model under which we did not own GPU computing
hardware within physical data center facilities and instead provided access to GPU compute capacity primarily through infrastructure made
available by the Aethir network. We have now expanded our business to purchase, own, and operate GPU computing hardware. This owned-asset
model is substantially more capital-intensive than our prior model and will require significant and growing capital expenditures to procure,
deploy, maintain, upgrade, and expand our infrastructure. We expect to fund these expenditures through a combination of customer deposits
and prepayments, cash from operations, and equity and debt financing, which may not be available to us on favorable terms, or at all.
If adequate financing is not available when required, we may be unable to acquire the hardware and infrastructure necessary to fulfill
our customer commitments or execute our growth strategy. If we raise additional funds through equity or convertible securities, our existing
stockholders may experience substantial dilution, and any such securities may have rights, preferences, and privileges senior to those
of our common stock.
The GPUs and related infrastructure we will now own are subject to rapid
technological obsolescence, and our results of operations depend on our ability to accurately estimate their useful lives and to
avoid impairment of these assets.
Unlike our prior model, in which we did not own the underlying compute hardware, we now bear the full
economic risk of the GPUs and related equipment we purchase. GPU technology is advancing rapidly, and newer generations of GPUs that offer
materially better performance, efficiency, or total cost of ownership are introduced frequently. As a result, the GPUs and related infrastructure
we will now own may become obsolete, decline in value, or generate lower pricing and utilization than we anticipate before the end of
their expected useful lives. We must make estimates regarding the useful lives of our computing equipment and our ability to redeploy
that equipment beyond the term of any initial customer contract, and we cannot guarantee that these estimates will prove accurate. If
our assumptions regarding useful lives, residual values, redeployment, or utilization prove incorrect, or if events or changes in circumstances
indicate that the carrying amount of our infrastructure may not be recoverable, we may be required to accelerate depreciation or record
material impairment charges, which could materially and adversely affect our reported financial results.
A substantial portion of our compute revenue is expected to be derived from a limited
number of customers and contracts, and the loss of, or non-performance by, any such customer would adversely affect our business.
We expect that, for the foreseeable future, a substantial portion of our compute revenue
will be concentrated among a small number of customers and contracts. This concentration exposes us to heightened counterparty
credit risk and to the risk of non-payment or non-performance, including in the event a customer experiences financial difficulty,
insolvency, or bankruptcy. Although our contract is structured on a take-or-pay basis and secured with a deposit, prepayment, and
monthly in-advance payments, we cannot assure you that a customer will perform its obligations, that the definitive agreement will
be enforceable in accordance with its terms, or that a customer will exercise any renewal option. The
loss of, a default by, a dispute with, or a significant reduction in spending by any one of our major customers, or our inability to
replace such revenue on comparable terms, could have a disproportionate adverse effect on our business, results of operations, and
financial condition.
Our compute business depends on the operation of dedicated data center facilities,
including the availability of reliable power and cooling, and operational failures at these facilities could materially disrupt our ability
to serve customers.
Our expanded business depends on deploying and operating owned GPU infrastructure within
dedicated data center facilities. The performance, availability, and delivery of our services depend on numerous factors, many of which
are outside our control, including the continued availability and functioning of power and cooling systems, the success or failure of
redundancy, disaster recovery, and business continuity systems, and decisions or failures by the third-party owners and operators of
the facilities in which our infrastructure is installed. Such data centers and associated infrastructure are also subject to risks of
damage, interruption, or destruction from power outages, equipment failures, fires, floods, natural disasters, physical or cybersecurity
attacks, human error, and other events. Because the deployment under our largest contract to date is concentrated in a single facility,
any prolonged outage, capacity constraint, or other disruption affecting that facility could prevent us from meeting contracted service
levels, expose us to service credits, penalties, or termination rights, and materially and adversely affect our business.
Our business could be harmed if we are unable to secure sufficient power, or by increases
in the cost of power or the imposition of new regulatory requirements on data center power consumption.
Operating owned GPU infrastructure requires access to substantial, reliable, and cost-effective electrical
power; our largest deployment to date requires 4.8 megawatts of committed power capacity alone. The rapid expansion of AI and large-scale
data center development has significantly increased electricity demand in certain markets, and policymakers, utilities, and regulators
are increasingly scrutinizing the impact of data centers on ratepayers, grid reliability, and the environment. We may face power outages,
shortages, capacity constraints, interconnection delays, or significant increases in the cost of securing power, any of which could limit
our ability to operate or expand our infrastructure. In addition, governments may impose new requirements on data center operators, including
obligations to fund grid upgrades, procure dedicated generation, enter into long-term capacity arrangements, accept curtailment during
periods of grid stress, or satisfy additional permitting, carbon reporting, or cost-allocation requirements, and may restrict, condition,
or delay new data center development. The global energy market has experienced significant volatility and inflationary pressure, and we
expect power costs to remain volatile and unpredictable. Any of these developments could increase our operating costs, impair our ability
to serve customers, delay our growth, and materially and adversely affect our business.
We depend on a limited number of suppliers, and primarily on NVIDIA, for the GPUs and
other hardware we purchase, and any supply disruption, delay, or price increase could impair our ability to deploy infrastructure and
fulfill customer commitments.
Our ability to acquire and deploy owned GPU infrastructure depends on our ability to procure GPUs
and related hardware in sufficient quantities, on acceptable terms, and within timeframes consistent with our customer commitments. We
source GPU hardware primarily from NVIDIA, which is currently the dominant supplier of GPUs used for AI training and inference, and we
do not manufacture any hardware ourselves. Reliance on a limited number of suppliers exposes us to a range of risks, including limited
availability of the latest-generation components, lack of control over production costs, delivery, and pricing, extended or unpredictable
lead times, the potential for binding price or purchase commitments at above-market rates, supplier prioritization of other customers,
and shifts in market-leading technologies away from those offered by our current suppliers. Our suppliers in turn rely on complex networks
of third-party suppliers, including semiconductor foundries such as Taiwan Semiconductor Manufacturing Company, and any disruption affecting
these upstream suppliers, whether due to geopolitical factors, capacity constraints, or natural disasters, could affect the availability
and cost of the hardware we require. The loss of or significant disruption to our access to NVIDIA GPU supply and related hardware, or
material price increases or extended delivery lead times, could delay our deployments, including our targeted third-quarter 2026 deployment,
reduce our available capacity, and materially and adversely affect our business.
We may be unable to deploy our owned infrastructure on the timelines we have committed,
and delays in deployment could result in penalties, lost revenue, or reputational harm.
Our largest contract to date contemplates a dedicated cluster purpose-built to the
customer's specifications, with a targeted deployment start in the third quarter of 2026. The procurement, integration,
configuration, and commissioning of large-scale GPU clusters and associated storage, networking, power, and cooling infrastructure
is complex and subject to numerous potential points of failure, including hardware delivery delays, facility readiness, the
availability of data center equipment such as switchgear, power distribution units, and cooling equipment, the availability of
skilled labor, and dependence on third-party facility operators and contractors. Our forward-looking statements regarding deployment
are subject to risks relating to the execution and enforceability of the definitive agreement, hardware supply chain constraints,
and facility readiness. If we are unable to deploy contracted infrastructure on the agreed schedule, we may be subject to service
credits, penalties, delayed or reduced revenue, customer disputes, termination rights, or reputational harm, any of which could
materially and adversely affect our business.
If customer demand is insufficient to utilize the capacity we build, or if we are unable
to redeploy infrastructure following the expiration or termination of a contract, we may not realize the expected returns on our capital
investments.
The owned-asset model requires us to commit substantial capital to acquire and deploy infrastructure,
often in advance of, or in reliance upon, specific customer contracts. Our expected returns depend on sustained customer demand and high
utilization of the capacity we build. If a customer reduces its usage, does not renew or terminates its contract, or if we are otherwise
unable to redeploy or resell capacity on economically attractive terms following the expiration of an initial contract term, we may experience
underutilized capacity, stranded assets, reduced margins, or impairment charges. Because our infrastructure is purpose-built and concentrated,
and because GPUs are subject to rapid obsolescence, we may be unable to repurpose assets for other customers or workloads without incurring
additional cost or delay. Any failure to achieve sufficient utilization of our owned infrastructure could materially and adversely affect
our business, results of operations, and financial condition.
We expect to incur indebtedness and to use secured or asset-backed financing structures
to fund our infrastructure, and our leverage could adversely affect our financial condition and flexibility.
To fund the acquisition of GPU infrastructure, we may incur substantial indebtedness and
may pursue secured financing arrangements, including asset-backed, equipment-financing, or other collateralized structures, in which our
GPUs and related assets serve as collateral. Companies in our industry carry significant indebtedness and finance GPU purchases through
delayed draw term loans, original equipment manufacturer financing arrangements, and similar structures secured by the depreciable cost
of GPU servers. A substantial level of indebtedness could require us to dedicate a significant portion of our cash flow to debt service,
increase our vulnerability to adverse economic and industry conditions, limit our ability to obtain additional financing, restrict our
operational and strategic flexibility through restrictive covenants, and expose us to the risk of acceleration or foreclosure on pledged
assets in the event of a default. The management of a more complex capital structure, including multiple layers of secured and unsecured
debt with differing covenants, maturities, and priorities, could increase our financial and operational risks and heighten the risk of
disputes among creditors. Rising or volatile interest rates would increase the cost of any floating-rate indebtedness, and we may be required
to enter into interest rate hedging arrangements that may not be effective.
We have a limited operating history operating an owned-infrastructure GPU business,
which makes it difficult to evaluate our business and prospects.
We have only recently expanded into purchasing, owning, and operating GPU computing infrastructure,
and we have a limited operating history under this business model. Our prior compute model was asset-light and distributed, and the owned-infrastructure
model requires different capabilities, including the procurement and lifecycle management of hardware, the operation of dedicated data
center deployments, the management of large multi-year take-or-pay contracts, and the management of capital-intensive financing. Our limited
experience delivering and managing longer-term, large-scale customer contracts may expose us to cost overruns, underutilized capacity,
performance obligations, service-level commitments, and other contractual liabilities. As a result, our historical results are not indicative
of our future performance, our future results may be difficult to predict and may fluctuate significantly from period to period, and you
should consider our business and prospects in light of the risks and uncertainties frequently encountered by companies operating in new
and rapidly evolving capital-intensive markets.
Updates to Existing Risk Factors
The energy and environmental demands of data centers and GPU compute infrastructure
may constrain the growth of the compute market and result in increased regulatory costs or operational limitations.
Data centers are significant consumers of electrical power, and this level of energy consumption
has attracted increasing scrutiny from regulators, utilities, and environmental groups, which may result in additional restrictions, permitting
requirements, carbon reporting obligations, or energy surcharges that increase the cost of GPU compute infrastructure. Because we will
now own and operate GPU computing infrastructure deployed in dedicated data center facilities that require substantial committed power,
including 4.8 megawatts of dedicated power for our largest deployment to date, constraints on available power capacity, increases in the
cost of power, and new regulatory or environmental requirements directly affect our operating costs and our ability to expand. In addition,
reputational and environmental, social, and governance concerns relating to the energy and water footprint of AI compute infrastructure
could adversely affect our business relationships, our access to capital, and our ability to obtain permits and approvals.
Geopolitical tensions and trade restrictions, particularly between the United States
and China, could disrupt GPU supply chains and limit our addressable market.
The global GPU compute market depends heavily on complex international supply chains,
including semiconductor manufacturing concentrated in Taiwan and South Korea, and geopolitical tensions between the United States
and China have already resulted in restrictions on the export of certain advanced semiconductors, including certain NVIDIA GPU
products. Because we will now own GPU hardware sourced primarily from NVIDIA, geopolitical tensions, tariffs, economic sanctions,
and export controls directly affect the cost, availability, and delivery lead times of the GPUs and related components we acquire.
Increasing use of tariffs and export controls has impacted, and may in the future impact, the availability and cost of GPUs and
other components, and expansion or reinterpretation of U.S. export controls covering advanced computing hardware could limit the
availability of components or require reconfiguration of our deployment plans. Any such disruption could increase our procurement
costs, delay our deployments, including our targeted third-quarter 2026 deployment, and materially and adversely affect our compute
business and our ability to execute our strategy.
Demand for GPU compute is highly concentrated, and a slowdown in AI-related spending
or the development of excess industry capacity could adversely affect our business.
A substantial portion of current and projected demand for GPU compute infrastructure is driven
by a small number of large technology companies and government-sponsored AI programs, and any significant reduction in their capital expenditures
could have a disproportionately negative impact on the broader GPU compute market. In addition, a substantial portion of our own compute
revenue is now expected to be derived from a limited number of customers and contracts, including our recently announced approximately
$260 million enterprise engagement. A slowdown, deferral, or reprioritization of AI-related customer spending, or the development of excess
industry capacity if anticipated AI workloads do not materialize, could result in pricing pressure, reduced utilization, longer sales
cycles, contract renegotiations, or impairment charges, any of which could be magnified by the capital-intensive, owned-asset nature of
our expanded business.
Advances in AI model efficiency could reduce demand for GPU compute, adversely affecting
the value of our compute business and our owned infrastructure.
A key driver of demand for GPU compute is the scale required to train and run AI models,
and consistent advances in AI model efficiency — such as new architectures, training techniques, or algorithmic improvements that
achieve equivalent or superior results using significantly less compute — could substantially reduce demand for raw GPU compute
capacity. Because we will own GPU hardware rather than relying solely on a distributed network, a significant and sustained reduction in
GPU compute demand could reduce the utilization, pricing, and resale or redeployment value of our owned infrastructure, and could require
us to recognize accelerated depreciation or impairment charges, in addition to adversely affecting the value of our ATH treasury holdings.
Security breaches and other disruptions affecting our infrastructure or the facilities
in which it is housed could compromise sensitive information and expose us to liability.
Our business requires that we collect and store sensitive data, and our information technology
and infrastructure are susceptible to attacks by hackers, viruses, employee error, malfeasance, or other activities. In addition, our
owned GPU computing infrastructure and the data center facilities in which it is deployed are subject to physical and cybersecurity risks,
including attacks by outside parties (whether private or state-backed), human error, malfeasance, insider threats, system vulnerabilities,
and inadequate security controls, any of which could result in service outages, unauthorized access to or loss of customer data and workloads,
or damage to our infrastructure. Our enterprise customers contract for dedicated infrastructure in part to ensure that their proprietary
data remains within a controlled facility boundary, and any physical or cybersecurity incident affecting our infrastructure or the facilities
in which it is housed could expose us to service-level penalties, contractual liability, loss of customers, regulatory exposure, and reputational
harm.
If our information technology and communications systems, or the infrastructure and
facilities on which our compute business depends, fail or experience a significant interruption, our business could be materially and
adversely affected.
The efficient operation of our business is dependent on information technology and communications
systems, the failure of which could disrupt our business and result in decreased revenue and increased overhead costs. Our expanded business
further depends on the continuous operation of owned GPU computing infrastructure housed in third-party data center facilities, and the
availability and performance of that infrastructure depend on power, cooling, network connectivity, redundancy systems (including N+1
redundant power), and the performance of the third-party operators of the facilities in which our equipment is installed. The failure
of any of these systems or services, including any failure of redundancy or disaster recovery measures, could prevent us from meeting
contracted service levels and could materially and adversely affect our reputation, business, and results of operations.
Our expansion into owned GPU infrastructure has materially increased our capital requirements
and our dependence on external financing.
We have a history of negative operating cash flows and have funded our operations in
part through at-the-market and private placement equity financings, with a significant portion of our liquidity held in ATH, a
digital asset whose market price has exhibited substantial volatility. Our expansion into purchasing and owning GPU computing
infrastructure has materially increased our capital expenditure requirements and our dependence on external financing, and our
liquidity needs are now driven in part by the substantial upfront and ongoing costs of acquiring, deploying, maintaining, and
expanding owned hardware and data center capacity. Although our largest contract to date is supported by a customer deposit,
prepayment, and monthly in-advance payments on a take-or-pay basis, these amounts may be insufficient to fund our capital
requirements, and our reliance on volatile sources of liquidity, including the price of ATH, may further constrain our ability to
fund these commitments.
