Cango Inc. (NYSE:CANG) Q3 2025 Earnings Call Transcript

Cango Inc. (NYSE:CANG) Q3 2025 Earnings Call Transcript December 1, 2025

Cango Inc. beats earnings expectations. Reported EPS is $0.19, expectations were $-0.2.

Operator: Good day, and welcome to the Cango Inc. Third Quarter 2025 Earnings Conference Call. [Operator Instructions] Please note today’s event is being recorded. I would now like to turn the conference over to Paul Yu, CEO. Please go ahead.

Peng Yu: Hello, everyone, and welcome to Cango’s third quarter 2025 Earnings Call. This quarter marks the 1-year anniversary of our strategic transformation into a Bitcoin miner, an important milestone for the company. Today, I will reveal our third quarter results and share how Cango continues to create long-term value in a rapidly changing market environment. During third quarter, we remain focused on our core mining operations further strengthening Cango’s position with the skilled and operationally disciplined Bitcoin manner. This is clearly reflected in our financial performance. In the third quarter total revenue reached USD 225 million, up 60.6% sequentially. Operating income was USD 43.5 million and net income was USD 37.3 million.

Today, Cango operates a deployed hashrate of 50 exahash globally, positioning us among the leading miners worldwide. In the third quarter, we produced 1,930.8 Bitcoins, averaging 21 Bitcoins per day, up 37.5% and in total output and 36% in daily production compared with the second quarter 2025. Leveraging our asset-light model we’ve built a competitive global footprint across the Americas, the Middle East and Africa in just 1 year. In our mining operations, we continue to execute our strategy to reprioritize hashrate optimization over expansion by refreshing older, less energy-efficient models to the T21 and S21 series and disciplined operations with significantly improved average operating hashrate, from 40.91 exahash in July to 44.85 exahash in September and further to 46.09 exahash in October, with efficiency surpassing 90%.

In August, we also acquired a 50-megawatt mining facility in the state of Georgia, lowering per unit operating costs and building dedicated energy infrastructure to support our long-term strategy. The current market environment remains volatile with significant fluctuations in Bitcoin prices. Cango is closely monitoring these dynamics, and we’ll continue to manage our deployed output and explore partnership models to mitigate market risks and enhance operating stability. While consolidating our core business, we also clarified our long-term strategy, building a global distributed AI compute network powered by green energy, with Bitcoin combining as a practical on ramp towards our energy and compute ambitions, following the sequence from Bitcoin mining to energy exercise and from operational depth to AI compute deployments.

In the third quarter were executed our phased road map with strict financial discipline, looking small-scale pilots with clear technical and IRR thresholds across both energy and AI compute. Our clean energy projects in Oman and in Indonesia are now underway and are expected to be commissioned within the next 1 or 2 years, providing strategic support for subsequent AI infrastructure development. The AI compute. In AI compute, Cango is taking a differentiated approach. Instead of building large centralized data centers, we focus on flexible distributed compute units in practical, this will integrate dispersed GPU resources into standardized compute pools and break them into smaller units tailored to the needs of small and midsized enterprises.

This approach is enabled by 2 core advantages our distributed operational expertise and our global energy footprint, allowing us to execute a unique asset-light first strategy. In terms of governance, we have assembled a new leadership team with deep experience in digital infrastructure and finance and completed the transmission from an APR listing to a direct listing on the NYSE to enhance transparency and reduce shareholder transaction costs. These initiatives provide strong support for our next phase of development. Lastly, let me briefly update you on our legacy business. Our used car export platform, AutoCango, delivered strong performance this quarter with revenue of USD 3.3 million, 90% sequentially. The platform remains asset-light and continues to scale, connecting buyers from Africa, the Middle East and Eastern Europe with quality vehicle inventory from China.

With that, I will now turn the call over to Michael Zhang, our Chief Financial Officer, to take you through the financials in more detail.

Yongyi Zhang: Thanks, Paul. Hello, everyone, and welcome to our third quarter 2025 earnings call. Before I begin the review of our financials, please note that starting this quarter, we will begin reporting U.S. dollars, which better reflects the profile of our revenue and profit following the divestiture of our charter asset in May 2025. Unless otherwise specified, all amounts discussed are in U.S. dollars. Total revenue in the third quarter of 2025 were $224.6 million, up 60.6% sequentially. Revenue from the Bitcoin mining business in the third quarter of 2025 was $220.9 million with a total of 1,930.8 Bitcoins mined during the period, up 50.9% and 37.5%, respectively, on a sequential basis. The average cost of mining Bitcoin, excluding depreciation of mining machines, was $81,072 per coin with all-in costs at $99,383 per coin.

Revenue from our automotive training business was $3.3 million in the third quarter of 2025. Now let’s move on to our cost and expenses during the quarter. Cost of revenues exclusive for depreciation in the third quarter 2025 was $162.6 million. Depreciation in the third quarter 2025 was $35.4 million. General and administrative expenses in the third quarter was $6 million. We recorded operating income of $43.5 million and net income of $37.3 million in the third quarter of 2025 compared with an operating loss of $1.2 million and a net loss of $9.5 million in the same period last year. On a non-GAAP basis, adjusted EBITDA for the third quarter of 2025 was $80.1 million compared with $1.2 million in the same period last year. Moving on to our balance sheet.

As of September 30, 2025, we had cash and cash equivalents of $44.9 million. Our balance sheet also reflects a $660 million receivables for Bitcoin collateral. In terms of operational assets, we carry our mining machine at a net value of $365.7 million of depreciation. On the liability side, we had $405.1 million in long-term debt owed to related parties. Together, these figures represent the core components of our financial structure as we closed the third quarter of 2025. This concludes our prepared remarks. Operator, we are now ready to take questions.

Q&A Session

Operator: [Operator Instructions] And today’s first question comes from Emerson Zao with Goldman Sachs.

Emerson Zhao: I have 2 questions. Number one, given the current Bitcoin prices, will the company consider selling Bitcoin holdings to fund new business expansion or manage market risk or support operation needs? And the second question is, you mentioned that equipment operates improved energy efficiency. But we see October operational hashrate, which was 46.6 exahash, which is still below the deployed hashrate of 50 exahash. So what are the main factors behind this gap? And when do you expect full utilization?

Yongyi Zhang: Thank you for your question. I think I would take the first one. This quarter, we continue to follow our mine and hold strategy, retaining all mined Bitcoin as part of our strategic reserve. We’ve seen a heightened volatility recently, driven by tight market liquidity and increased uncertainty around the U.S. rate cut parts. However, we believe the fundamental thesis for Bitcoin as core reserve assets remain intact under broader macro spectrum. We will take a flexible approach across that equity and other financing channels to support our development of our new initiatives. Our Bitcoin reserves also provide a meaningful liquidity buffer and optionality for structured financing if needed.

Peng Yu: Thank you for your question. I’m going to answer the question regarding the operation efficiency. After completing the acquisition of 18 exahash in late June, we reached full scale operations at safe for the first time in July during the initial integration phase we experienced temporary downtime due to cross state machine relocations and ongoing power system commissioning at the newly acquired sites. This factor created a short-term pressure on our time. Our operations team responded quickly and throw system-level optimization uptime has now stabilized about 90%, which is considered industry-leading and demonstrating the strength of our operational capabilities. It is important to note that external factors such as experience weather and great curtailment periodically affect minor availability.

This is an industry-wide reality and achieving 100% uptime is not visible. Among comparable industry peers uptime about 90% is regarded as a strong performance benchmark. Going forward, we will continue enhancing efficiency through upgrade to our intelligent operations and maternal system while replacing low efficiency, however, will improve plant.

Operator: Our next question comes from Pingyue Wu with Citic Securities.

Pingyue Wu: This is Pingyue from Citic Securities. And I have 2 questions. The first question is related to the debt structure. And the company mentioned converting short-term debt into long-term debt. Can you elaborate on the financial benefit of this shift? And what is your current cost of debt? And secondly, my question is related to CapEx. Some capital-intensive data center operators have undergone significant value reset. Some people are questioning whether AI CapEx is entering bubble in territory. Given that you are now entering into the AI infrastructure space, how do you view this risk?

Yongyi Zhang: Thank you for your questions. And I will take the first one. Through this optimization of our debt maturity profile, our liability now primarily composed of long-term borrowings. This better aligns our capital structure with our strategic strategy of building big oil reserves through self-mining, enhancing balance sheet stability and reducing financial risk. At present, we plan borrowing costs remain in the 7% to 8% annualized range at this level is expected to remain stable following the maturity structure adjustment.

Peng Yu: Regarding the second question, I think it’s true that the market is reassessing returns on AI investments, particularly for hyperscale data centers with high leverage heavy CapEx and long contract cycles, but the demand level, AI influence and industry-specific applications are still expanding rapidly the demand mix may evolve, but long-term compute demand is not appearing. In turning later, gives us the benefit of observing market shifts and avoiding high leverage expansion at the end of the previous cycle, our advantage slicing a lighter asset and leverage structure and a more distributed edge-oriented operating footprint. We evaluate and monitor AI project investments, potential returns and cash flow profiles at every stage. This allows us to dynamically adjust course, optimize capital efficiency and preserve strategic feasibility at all times.

Operator: Our next question comes from [ Joey Chai ] with [ Wujen ] Securities.

Unknown Analyst: I have 2 questions as well. The first one, Bitcoin has pulled back sharply from its all-time high in October. How does this affect your operating pace for Q4 in 2026. With your current cash position in BTC Holdings, how long can you operate under extreme market conditions? And do you have a worst case plan? And the second one, the Georgia site is self-owned and this contradicts the asset-light model. Will future expansion favor on the sites or leased sites?

Yongyi Zhang: Well, thank you for your questions. Yes, we conduct frequent internal stress tests. And thanks to our asset-light models and operational flexibility we can dynamically adjust and even shut down high-cost sites on the extreme scenario to reallocate harsh power and control operating expenses. And we have the flexibility to adjust our BTC Holdings strategy as needed. We focus on long-term return per unit of harsh power as a long-term economics of Bitcoin rather than short-term market noise.

Peng Yu: Regarding the Georgia side, it’s important to clarify that. Today, acquisition is not a strategic bet, but rather an upgrade of our SLI model, we choose to acquire the site because it aligns with our long-term needs around securing low-cost power, gaining great stability and deepening our infrastructure operations capabilities. Looking ahead, we will continue to follow a balanced model of lease first with selected selective strategic acquisitions. These things will remain our primary path for rapid expansion and geographic diversification we evaluate potential acquisitions against strict criteria, power cost, stability for AI grade data center upgrades and regulatory stability We believe only a portion of 3 sites is essential to maintaining long-term cost advantages and supporting our strategic transition.

On capital allocation, we prioritized efficiency over share scale. All cash flows will be direct to first to initiatives that strengthen our structure cost advantages such as acquiring sites to lower power costs or upgrading underperforming compute equipment. At the same time, we remain disciplined in managing our asset structure, evaluating and monitoring leverage and financial discipline through ranges, financial and operational metrics.

Operator: And our next question comes from Kevin Dede at H.C. Wainwright.

Unknown Analyst: This is [ Daniel Malin ] on for Kevin Dede. We’re curious how Cango feels it’s best to address the HPC market, whether that be through cloud compute or a power shell model. And if the recent pullback in Bitcoin could it all accelerate this? And how are you guys thinking about time lines with those 2 ventures?

Peng Yu: Thank you for your question. In AI compute, Cango is taking a differentiated approach instead of building large centralized data center. We focus our black for distributed compute units in practice, this will integrate dispersed GPU resources into standardized compute pools and break them into smaller units tailored to the needs of small and midsized enterprises. This approach is enabled by 2 core advantages; our distributed operational expertise and our global energy footprint, allowing us to execute a unique SLI first strategy.

Operator: Thank you. That’s all the questions we have time for today. And this concludes today’s conference call. We thank you all for attending today’s presentation. You may now disconnect your lines, and have a wonderful day.