SAN FRANCISCO, July 08, 2026 (GLOBE NEWSWIRE) -- Sunrun (NASDAQ:RUN), America's largest provider of home battery storage, solar, and home-to-grid power plants, today launched a distributed AI compute pilot program. The pilot marks Sunrun's first step into distributed edge computing, a new business category that the company believes represents a high-margin revenue opportunity leveraging its existing energy infrastructure, large customer base, and grid service capabilities.

Following a successful proof of concept that demonstrated revenue generation and high demand for distributed compute, Sunrun is expanding the pilot to place numerous compute nodes in homes equipped with Sunrun solar and battery storage systems. Sunrun is coordinating the selling of inference capacity to enterprise compute buyers, while also testing the nodes under a variety of conditions and rate structures to gather operational data and information. Participating homeowners are compensated for hosting the compute nodes.

"AI companies are scrambling to secure greater access to energy and computing power," said Sunrun President and Chief Revenue Officer Paul Dickson. "Over nearly two decades, we have perfected our ability to operationalize, finance, and scale distributed assets. We are now using our leadership position in distributed home energy and proven infrastructure to bring compute closer to the sources of energy and inference."

AI inference demand is growing at approximately 35% annually and is projected by McKinsey to surpass training as the dominant AI workload by 2030, representing more than half of all AI compute. Unlike AI training — which requires massive, tightly synchronized clusters — inference is modular, geographically distributable, and highly sensitive to latency. That makes it a natural fit for edge deployment close to end users, and a natural fit for Sunrun.

Sunrun's distributed footprint of more than 1.1 million existing customers represent an addressable deployment base and gives the company a structural advantage hyperscalers can’t quickly replicate. Where a traditional data center can take years to permit, build, and interconnect, Sunrun's distributed deployment model can add significant inference capacity in a fraction of the time.

Advantages of Sunrun's Distributed Compute Model

Just as Sunrun has helped democratize energy by enabling households to generate, store, and share their own power, this distributed data center model enables American households to play a direct role in powering the nation's AI future and share in the economic opportunity it creates. For hyperscalers, it provides a flexible, scalable source of compute capacity that complements centralized data centers and accelerates AI deployment.

Geographic Flexibility: By placing compute nodes behind the meter, Sunrun mitigates regional threats of rising utility rates, overloaded grids, and power supply shortages.
Scale With New and Existing Customers: Sunrun can reach meaningful compute scale across its growing customer base of over 1.1 million nationwide without the lead time of new data center development.
Speed to Compute: Deployed in the built environment, Sunrun's distributed nodes eliminate land acquisition, transmission buildout, and utility interconnection queues.
Existing Service Infrastructure: Sunrun already monitors and services energy equipment on more than a million homes — an operational foundation immediately available to support distributed compute at scale.
Backup Power: Distributed compute nodes are paired with Sunrun's onsite battery systems, allowing data processing to continue operations through certain grid outages.
Grid Resilience, Not Grid Strain: Rather than adding load pressure to already congested regions, Sunrun's distributed model improves utilization of existing electrical infrastructure, turning the network into a grid asset as well as a compute asset.
Maximizing System Value: Sunrun's systems and controls optimize the compute nodes in concert with the customer’s energy consumption patterns, participation in grid services, and the customer’s electricity rate structure.
Customer Compensation: Consistent with Sunrun's strategy to expand customer value, participants are compensated for hosting compute nodes, extending Sunrun's value proposition and strengthening customer retention.

Sunrun’s distributed compute pilot is a distinct and separate initiative, but complements the company’s recently announced agreement with Renew Home and Tesla to aggregate more than 16 gigawatts of flexible home energy capacity for hyperscalers and utilities. Compute capacity deployed onsite at customer homes can serve the same surging AI demand that is driving hyperscalers to seek every available path to new energy capacity.

Sunrun expects to complete the pilot over the coming months and will assess results against defined milestones, compute performance, and homeowner experience before determining the scale, speed and customer offering of a broader rollout. The company is actively in discussions with enterprise compute offtakers, homebuilders, and utility partners to structure the commercial and deployment frameworks that would support expansion.

To learn more and join the waitlist, visit sunrun.com/compute.

About Sunrun

Sunrun Inc. (NASDAQ:RUN) is America’s largest provider of home battery storage, solar, and home-to-grid power plants. As the pioneer of home energy systems offered through a no-upfront-cost subscription model, Sunrun empowers customers nationwide with greater energy control, security, and independence. Sunrun supports the grid by providing on-demand dispatchable power that helps prevent blackouts and lowers energy costs. Learn more at www.sunrun.com.

Media Contact

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press@sunrun.com

Investor & Analyst Contact

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Forward-Looking Statements

This communication contains forward-looking statements related to Sunrun (the "Company") within the meaning of Section 27A of the Securities Act of 1933, Section 21E of the Securities Exchange Act of 1934, and the Private Securities Litigation Reform Act of 1995.

Forward-looking statements include, but are not limited to, statements regarding the Company’s residential distributed AI compute pilot program; the Company’s expectations regarding distributed edge computing, AI inference demand, and enterprise compute buyer demand; the potential availability, timing, scale, performance, utilization, reliability, and benefits of distributed compute capacity deployed in homes; the Company’s ability to leverage its existing customer base, solar and battery storage systems, energy infrastructure, monitoring and service infrastructure, grid service capabilities, and customer relationships to support distributed compute operations; the Company’s expectations regarding customer value, homeowner participation, homeowner compensation, customer retention, and homeowner experience; the potential for the pilot or any broader rollout to generate revenue, margin, customer value, or other commercial benefits; the Company’s expectations regarding proof-of-concept results, operational data, rate structures, pilot milestones, compute performance, and future commercial frameworks; the Company’s ability to coordinate the sale of inference capacity to enterprise compute buyers; the Company’s discussions with enterprise compute offtakers, homebuilders, utilities, and other potential partners; the potential expansion, timing, speed, customer offering, and scale of the pilot or any broader deployment; the anticipated advantages of distributed compute compared to traditional data centers, including potential deployment speed, geographic flexibility, grid utilization, infrastructure requirements, real estate needs, transmission needs, utility interconnection requirements, backup power support, and system value; the expected relationship between the distributed compute pilot and the Company’s other distributed energy resource, grid services, home-to-grid, and distributed power plant initiatives; the Company’s strategy, market leadership, competitive position, business plan, new products, new services, new technologies, customer value proposition, market opportunity, and ability to scale offerings; and anticipated demand, market acceptance, and market adoption of the Company’s offerings.

Words such as "believe," "expect," "continue," "project," "seek," "will," "would," and similar expressions are intended to identify forward-looking statements, although not all forward-looking statements contain these identifying words.

These statements are not guarantees of future performance; they reflect the Company’s current views with respect to future events and are based on assumptions and estimates and are subject to known and unknown risks, uncertainties, and other factors that may cause actual results, performance, achievements, or outcomes to be materially different from expectations or results projected or implied by forward-looking statements.

The risks and uncertainties that could cause the Company’s results to differ materially from those expressed or implied by such forward-looking statements include, but are not limited to: the Company’s ability to complete the pilot successfully or at all; the timing, cost, technical performance, reliability, utilization, and commercial performance of compute nodes and related software, hardware, networking, telemetry, monitoring, and control systems; customer eligibility, customer authorization, homeowner participation, homeowner experience, customer retention, and customer compensation; compute node availability, performance, interoperability, and dispatch accuracy; market demand from enterprise compute buyers, hyperscalers, utilities, homebuilders, and other potential customers or partners; the ability to negotiate, enter into, and perform commercial arrangements with compute offtakers, homeowners, utilities, homebuilders, and other partners; the availability, quality, cost, and performance of compute nodes, software, networking, and other technology needed to operate distributed in-home compute capacity; data security, cybersecurity, and information control requirements and risks; outages, service interruptions, equipment failures, customer premises conditions, installation constraints, permitting requirements, and other operational risks; changes in utility rate structures, power market conditions, grid services program requirements, utility partner requirements, and in-home deployment requirements and other regulatory or policy frameworks; potential local, state, federal, utility, homeowner association, zoning, electrical code, building code, telecommunications, environmental, health, safety, and other requirements applicable to in-home compute deployments; the Company’s ability to manage costs, maintain quality, compete effectively, and scale new offerings; the Company’s ability to attract and retain business partners; changes in retail electricity prices and power market conditions; factors affecting the market for distributed energy resources, grid services, data centers, AI inference, and compute infrastructure; and such other risks and uncertainties identified in the reports that the Company files with the U.S. Securities and Exchange Commission from time to time, including the Company’s Annual Report on Form 10-K for the fiscal year ended December 31, 2025 and subsequent Quarterly Reports on Form 10-Q.

All forward-looking statements used herein are based on information available to the Company as of the date hereof, and the Company assumes no obligation to update publicly these forward-looking statements for any reason, except as required by law.

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