Cango Inc.

Good evening and welcome to the Cango Inc. fourth quarter and full year 2025 earnings conference call. All participants will be in listen-only mode. Should you need assistance, please signal a conference specialist by pressing the star key followed by zero. After today's presentation, there will be an opportunity to ask questions. Please note this event is being recorded. I would now like to turn the conference over to Mr. Paul Yu, Chief Executive Officer. Please go ahead.

Thank you. Hello everyone and welcome to Kangol's fourth quarter and full year 2025 earnings call. 2025 marks a landmark year in our company's history. Our first year of transformation since pivoting to Bitcoin mining in November 2024. It was a year of accelerated execution and we accomplished several critical objectives. First, asset restructuring and global deployment through a series of transactions. We relocated our asset from traditional auto finance business to our Bitcoin mining operations within six months. This helped us build a global distributed mining network. Second, leadership and management to align with our new strategy we have strengthened our board and management team with seasoned industry professionals. They have brought deep expertise and established networks in both digital assets and infrastructure, which has sharpened our competitive edge in the sector. Third, listing structure optimization. During the year, we transitioned from an ADR listing to a direct stock listing. This move lays a solid foundation for us to access a broader range of capital market tools, reach a broader base of investors, and reduce holding costs for existing shareholders. Operationally, 2025 showed a clear execution discipline despite significant market volatility in the second half of the year. We maintained professional standards across core metrics, including hash rate scale, Bitcoin production, and miner uptime. In the fourth quarter of 2025, we recorded total revenue of 179 million and produced 1,718.3 Bitcoin. For the full year, total revenue reached $688 million, with Bitcoin production totaling $6,595.6. As the economy of scale took hold, we achieved strong revenue growth and posted positive EBITDA for the full year. The net loss attributable to shareholders for 2025 was $622 million, mainly due to the following factors. First, some non-recurring transformation costs. This includes a one-time book loss of around $169 million from discontinued operations. Then a further loss of $257 million came from impairment loss. from mining equipment and the company acquired and settled in FT triggered by us by the significant appreciation in Congo's share price between sending and delivery. Second, towards the end of fourth quarter, the price of Bitcoin and other cryptocurrencies declined sharply, driven by external macroeconomic factors. and geopolitical tensions. This resulted in a fair value loss of 96.5 million on our Bitcoin holdings and an additional impairment provision of 81 million on mining machines as a result of the downward price impact on their fair value. In the early stages of our transformation, by our CapEx capabilities. We adopted a collocation model to rapidly secure a large share of the Bitcoin network hash rate. We quickly built a hash rate of 50 extra hash per second, capturing approximately four to five of the global network. However, competition intensified globally. and our cash cost per Bitcoin mined approached a high of 84,000 in the fourth quarter, 2025. Recognizing further price pressure, we're heading into 2026. We took prudent action. We reduced debt exposure, recovered liquidity, and began phasing out in efficient capacity. These steps have strengthened our balance sheet and enhanced operational efficiency as we enter the new year. In February 2026, we strategically sold 4,451 Bitcoin from inventory and used the proceeds to repay loans, reducing our overall debt. We then completed 10.5 million capital injection from shareholders. Additionally, we signed agreement with Armada New Network Limited and Fortune Peak Limited for new funding around totaling 65 million. We expect these steps to progressively strengthen our FTA base and mitigate potential market volatility risks going forward. On the operation side, we are optimizing our operations by phasing out older high energy consuming mining machines. We're also gradually moving our computing power to regions with lower electricity price. Well, this will lead to a contraction in our total head rate scale in the short term. It will effectively improve the energy efficiency of our overall fleet, lower cost per coin, and enhancing our resilience against drastic market fluctuations. Finally, many of you have asked about our AI business transformation, our efforts to reduce existing debt, strengthen equity capital, and optimize Bitcoin mining operations have created the necessary flexibility to really make progress on AI. On that note, we have officially established EcoHash, a wholly owned subsidiary based in Texas dedicated to high performance computing and AI inference. leveraging our accumulated experience in large-scale deployment and management of distributed computing infrastructure, as well as our broadly partnered globally energy network of Bitcoin mining sites. We will launch standardized modular AI computing nodes, aiming to provide highly flexible and cost-effective solutions for long-term AI inference demand. As of today, we are making steady progress on feasibility studies and preparatory work. Let me share a few updates. On the infrastructure front, we have initiated the first phase retrofit of our own LN site in Georgia, USA for standardized AI nodes deployment. On the product side, our containerized GPU computing solutions also reached the leverage deliverable stage. Our objective is to leveraging our existing accessible skilled energy network to provide flexible and intelligent computing power to support the digital economy. In 2025, we demonstrated the speed of our transformation. In 2026, we will demonstrate our resilience and our ability to adapt and evolve. While the current microeconomic environment presents challenges, we also see long-term opportunity. The logic behind our decisions is clear. Proactive adjustment, disciplined execution, and commitment to the AI era. With that, I will turn the call to Michael Zhang, our chief financial officer, to take you through the financials in more detail.

Thanks, Paul. Hello, everyone, and welcome to our fourth quarter and four-year 2025 earnings call. Before I started to review our financials, please note that unless otherwise stated, all amounts discussed are in U.S. dollars. Total revenue in the first quarter was $179.5 million. For the four-year, revenue reached $688.1 million. Revenue during the quarter from the Bitcoin mining business was $172.4 million, with a total of 1,718.3 Bitcoins mined during the period. The average cost to mine Bitcoin excluding depreciation of mining machine was $84,552 per coin, with owing cost of 106,251 per coin. For the full year, revenue from the Bitcoin mining business was 675.5 million with a total of 6,594.6 Bitcoins mined during the year. The average cost to mine Bitcoin excluding depreciation of mining machine was 79,707 per coin with owing cost at 7,272 per coin. Revenue from our automobile trading business was 4.8 million in the fourth quarter and 9.8 million for the four year. Now let's move on to our cost and expenses. Cost of revenue exclusive of depreciation in the first quarter was 155.3 million and 543.3 million for the four year. Depreciation in the fourth quarter was $38.1 million and $116.6 million for the four-year. General and administrative expenses in the fourth quarter was $9.9 million and $28.9 million for the four-year. Impairment loss from mining machines in the fourth quarter was $81.4 million and $338.3 million for the four-year. loss from changing fair value of receivable for bitcoin collateral in the fourth quarter was 171.4 million and 96.5 million for the full year operating loss for the for the quarter was 276.6 million with a net loss from continuing operations of 285 million in the fourth quarter for the full year the operating loss was $437.1 million, and net loss from continuing operation was $452.8 million. On a non-GAAP basis, adjusted EBITDA for the full year was $24.5 million. Moving on to our balance sheet, as of December 31, 2025, we had cash and cash equivalents of $41.2 million. Our balance sheet also includes $663 million of receivables, or Bitcoin collateral. In terms of operational assets, we carry out mining machine at a net value of $248.7 million of depreciation. On the liability side, we had $557.6 million in long-term debts. Together, these figures represent a core component of our financial structure as we close the fourth quarter of 2025. This concludes our prepared remarks. Operator, we are now ready to take questions.

We will now begin the question and answer session. To ask a question, you may press star then one on your touch tone phone. If you're using a speakerphone, please pick up your handset before pressing the key. To withdraw your question, please press star then two. If you would like to state your question in Chinese, you may do so, but then please also restate your question in English. Your first question today comes from Pinyue Wu with SETI-C Securities. Please go ahead.

Hi. Thank you, management team, for taking my question. This is Pinyue from SETI-C Securities. And my first question is, the company recently launched EchoHash, a subsidiary focused on HPC and AI inference compute service. And how do EchoHash position itself in a highly competitive AI compute market? And what is the core logic behind our approach compared with traditional data centers? Thank you.

Thank you for your question. EchoHash is not designed to replace traditional high-profile data centers. Instead, we focus on targeted opportunities within specific segments of the AI compute market. Hyper-scale facilities are built for large-scale centralized model training workloads. Those projects require significant upfront capital and construction timelines that can span several years. By contrast, our initial focus is on AI inference and generative AI workloads. These use cases have distributed demand and are sensitive to latency. These use cases often require flexible deployment of compute nodes closer to end users rather than relying solely on massive centralized facilities. Our approach centers on resource reuse and modular design, notably we can leverage our global energy network connected to our existing Bitcoin mining sites. From this space, we are deploying standardized and modular AI compute nodes that can be deployed much faster than traditional data center infrastructure. This model shortens timelines, lowers upfront construction costs, and delivers compute capacity more efficiently. For now, EcoHash remains in early phase of model validations and technical integration. We are taking a major approach. Our primary objective is to explore how we can fully leverage our existing energy infrastructure to participate in the rapidly growing AI inference market. with a model that is asset-light, quick to deploy, and able to deliver stronger capital efficiency. Thank you.

Thank you. And my second question is, the company sold more than half of its Bitcoin holdings in February 2006. And this appears to be a notable shift from the mine and hold strategy highlighted in the third quarter. And my question is, what drives this decision? Thank you.

Thank you for your question. Actually, we understand that investors are watching this shift very closely. From a financial management perspective, our shift from a pure Bitcoin accumulation strategy toward more strategic monetization reflects our focus on maintaining balance sheet strength in a current market environment. Given the heightened volatility in Bitcoin prices since late in the fourth quarter and into early 2026, We made a decision in February to monetize a portion of our Bitcoin holdings. The objective was to reduce financial leverage and further optimize our balance sheet, ensuring that the company remains well positioned to then navigate potential continued market volatility. It is also worth noting that we are seeing a broader shift across the mining industry. In a cyclical environment with increasing volatility, Maintaining excessive exposure to a single asset can introduce unnecessary balance sheet risk. As a result, a more balanced approach between long-term asset exposure and financial stability is becoming increasingly common across the sector. At the same time, the company is entering a critical phase in validating the diversification of our computing power business. We see AI computing as an important long-term growth By making this strategic adjustment, we are also creating greater financial and operational flexibility to support continued development and scaling of our AI-related initiatives. Thank you.

Thank you. Thank you very much.

Your next question comes from Ming Zhang with China Securities. Please go ahead.

Morning, this is John from CITIC. Thanks for this opportunity. I have two questions. The first one is that we noticed that the company's leverage ratio remained relatively high at the end of the reporting period, and the Bitcoin practice has been volatile recently. And if the price remains weak, how will the company fund the development of its AI bill list? You mentioned that $10.5 million capital injection from the controlling shareholders and $16.5 million equity financing arrangement. How will this fund be allocated between the mining bill and the AI initiatives in 2026? And the second question is that regarding the development of AI compute, let's work. What is the expected over the next year? And when could the billions begin contributing for ? That's my question. Thank you.

Thank you. I will take your first question. We have taken proactive steps to strengthen our balance sheet, as I just mentioned. We recently sold 4,451 bitcoins from inventory and used the proceeds to partially repay outstanding loans. This reduced our overall financial leverage and increased flexibility as we advanced our AR initiatives. At the same time, we completed the closing of our US$10.1 million capital injection and entered into agreement with Amada Network Limited and Fortune Peak Limited for an additional US$65 million equity investment. Once this new round of financing is completed, the company's leverage ratio will decline further, resulting in a stronger balance sheet that better support the development of our AI business. For the AI segment, we intend to follow a disciplined and phased investment strategy. Phase one is product and business model validation. During this stage, we will rely primarily on internal capital. We will conduct pilot infrastructure upgrades and deploy compute products at our own LN mining site. Phase two begins once the model is validated. We plan to establish several backbone nodes in collaboration with selected partner mining facility. In these cases, infrastructure upgrades will be carried out jointly with site operators and the project level structure financing such as GPU backed financing may be used to support expansion. Phase three occurs as the computer Network gradually forms and begins generating stable operating cash flow. At that point, we expect to use a flexible mix of equity and debt financing to fund the next stage of growth. Thank you.

Regarding the AI timeline, our approach to the AI business remains measured and pragmatic. The initiative is still in the early stages. So our near-term focus is on validating the commercial models and evaluating unit economics. Given where we are in the pilot phase, it would be premature to issue specific revenue forecasts at this time. Currently, our most tangible progress is taking place at our self-operated LN mining site in Georgia. We are conducting a small scale pilot project to deploy the first batch of standardized AI compute nodes there. This will allow us to validate the technical architecture and gather operational data. The border 1.2 gigawatt energy network that we can access serves a long-term strategic resource pool. However, This represents a medium to long-term capacity option. It is not necessarily a commitment to immediate large-scale capital expenditure. For now, we are focused on gradually validating the model through the Georgia pilot while ensuring that overall liquidity and financial stability remain intact. Thank you.

Thank you. Your next question comes from Marco Zhang with Geelongi Research. Please go ahead.

Hi, this is Marco from Kunahui. Thanks for taking my question. Congrats on your successful transformation last year. I have two questions here. First, you increased your hash rate from 32x hash per second to 50 in 2025. So do you have specific hash rate expansion targets for 2026?

For 2026, our focus is efficiency. rather than scale. Our goal is to maintain a healthy cash flow and strong risk resilience across market cycles. In 2025, we produced from Mixi approximately 6,600 BTC, which validated the strength of our existing operational footprint. For 2026, we will implement a prioritized efficiency strategy. This starts with systematically phasing out older high energy consumption mining rigs. We will also gradually relocate some of our hash rate to regions with more competitive electricity pricing. This optimization may result in a temporary reduction in total hash rate in the near term. However, it will greatly improve fleet-wide energy efficiency, lower cost per Bitcoin mined, and strengthen our resilience during periods of volatility. Our objective is to build a more resilient compute portfolio by phasing out inefficient capacity and freezing up liquidity We strengthen our balance sheet. This also preserves capital resources that may later support our ongoing AI transition. Thank you.

Got it. Thanks. My second question is for our modeling purpose, looking ahead from your perspective, How should investors evaluate Kangal's valuation framework in 2026 and beyond? Should the company be viewed primarily as a mining company or as an AI infrastructure provider? Thanks.

Thank you for your question. Bitcoin mining remains our foundation, while AI represents our incremental growth engine. Over time, we believe investors may increasingly evaluate our performance through metrics such as revenue per megawatt. Whether we are deploying power into Bitcoin money or AI compute, the underlying principle is the same. Converting energy into economic value, we will allocate resources toward whichever segment delivers the stronger returns. In that sense, Tango is evolving into a flexible compute platform. We can dynamically allocate energy-backed compute capacity across different market-based return potential. Thank you.

The next question comes from Kevin Dede with HC Wainwright. Please go ahead.

Hi, Paul. Hi, Michael. Thank you so much for having me on the call. I'd like to quiz you a little bit more, Paul, please, on detail behind your AI pilot in Georgia. How long do you think it will take you to validate the model? And do you think you might be able to turn to live market revenue sometime within this calendar year?

Hi, Kevin. This is Simon Tang, Chief Investment Officer here. I'll step in and take this question if that's okay.

You're perfect, Simon. Thank you.

Hi, great to reconnect. In terms of the AI pilot in Georgia, because this is going to be a modular containerized solution, so it should be relatively quick. We anticipate that from breaking ground to Overall, coming on stream, it should take somewhere between four to six months, and this is a relatively conservative estimate. And secondly, to answer a second question, in terms of revenue generation within this year, yes, we do anticipate that there is going to be some sort of revenue generated from this business model this year.

Okay. Simon, as you look at optimizing the Bitcoin mining fleet, How much of your 50 exahash would you classify as inefficient? And how much capital do you think you'll be able to allocate toward replacing the fleet versus investment in AI infrastructure?

Got it. When we talk about inefficient, it's a function of both the mining machine model as well as the power price that we have in place for that particular site, right? So it's very difficult for us to quantify at the moment holistically how much of that we would classify as inefficient. But overall, in terms of the general direction of this business, as Paul and Michael have alluded to earlier, we're looking at a variety of ways to increase the economics and outcome of this business, whether it be swapping some of these machines for newer models, or whether it be moving them to more cost-efficient sites, or whether it be through renegotiating some of these contracts, which are either expiring or which are just generally being renegotiated as well. And in terms of the capital allocation for this effort, I think in terms of new capital investment is going to be more geared on the AI side. So on the mining machine side, currently we do not have any significant plans for allocating more investment into procuring new machines.

Okay. The auto business seemed to kick up pretty nicely in the fourth quarter, and I was hoping you could help me understand whether or not there was some seasonality there, how you would expect this year, 2026, to progress. Do you think you should see an overall lifting in revenue there? And then Please give us some indication of where you are on profitability in that business.

Thank you, Kevin, for your question. I think, yes, we see that there is a very quick development of our overseas auto trading business overall. And we do expect that there is still got a significant growth related to that sector in the coming year. But as Simon just mentioned, since we allocate the majority of our capital into the AR sectors, I mean, the AR initiatives. So we don't, we do not expect that we will allocate the further capital into the auto trading sectors. So it's actually, it's a type of, I mean, internal growth. I mean, the genetical growth by our, I mean, the auto trading business line itself. So I think, yeah, and also it's also related to the demand side. You know that there is due to the Joe political reasons and actually the price volatility related to the energy. So I think it's very difficult for us to give a very clear view about the performance, the financial performance for the automobile trading business in the next year. Thank you.

Thank you, Michael, for taking my questions. I appreciate it. Paul, I'd like to offer my congratulations. It's really pretty amazing on how quickly you were able to transform the company. And I have no doubt that you'll be able to work out all the problems you may run into in addressing HPC and AI. So congratulations on all the progress and good luck in the future.

Thank you, Kevin. Thank you for your time.

Your next question comes from William Grigoski with Green Ridge Global. Please go ahead.

Hi, thanks. I just wanted to ask about how much of the Georgia facility is being allocated to the phase one pilot? And are you able to give some kind of rough sense as to how much money is being spent on that phase one pilot?

Hi, Bill. This is Juliet. Thank you for your question. I'll try to take this one. So with regard to the LN site, we're currently starting the reprofiling work for the site, basically because we're actually adopting a modular kind of like approach. So we don't expect to turn like a major kind of like hash rate or megawatt into AI at this stage. So that one should be used as a showcase. So we will say one to two megawatts to show the possibility, to show the things we can do with our existing infrastructure. So in terms of CAPEX, so basically we've been running demo projects as we actually discussed in previous course last year in terms of AI transition. So we are thinking of like a ballpark of around like 20 million for one megawatt, including GPU. So just in case. So it's still in the process of feasibility study. So we will show more details, including numbers, when we have the LN site ready, probably later this year, as just mentioned by Simon. So for the re-trophing work, it might take around like 46 months in a kind of like conservative approach. I hope that answers your question. Thank you.

Yes, thank you.

Thank you. This concludes our question and answer session. I would like to turn the conference back over for any closing remarks.

Thank you for joining us. We're good.

Thank you very much. Thank you, everyone, for joining our earnings call today. Thank you.

The conference has now concluded. Thank you for attending today's presentation. You may now disconnect.