MARA Holdings Inc (MARA) 2025 Q3 法說會逐字稿

Greetings and welcome to MARA's Q3 2025 earnings conference call. (Operator Instructions) Please note, this conference is being recorded.

各位好，歡迎參加 MARA 2025 年第三季財報電話會議。（操作員說明）請注意，本次會議正在錄音。

I will now turn the conference over to Robert Samuels, VP of Investor Relations. Thank you. You may begin.

現在我將把會議交給投資者關係副總裁羅伯特·塞繆爾斯。謝謝。你可以開始了。

Thank you, operator. Good morning, and welcome to Mara's third-quarter 2025 earnings call. Thank you for joining us today. With me on today's call are our Chairman and Chief Executive Officer, Fred Thiel; and our Chief Financial Officer, Salman Khan. Today's call includes forward-looking statements, including those about our growth plans, liquidity and financial performance. These involve risks and uncertainties, and actual results may differ materially. We disclaim any obligation to update these statements, except as required by law. For more details, see the Risk Factors section of our latest 10-K and other SEC filings.

謝謝接線生。早上好，歡迎參加 Mara 2025 年第三季財報電話會議。感謝您今天蒞臨。今天與我一起參加電話會議的有我們的董事長兼執行長弗雷德·蒂爾，以及我們的財務長薩爾曼·汗。今天的電話會議包含前瞻性陳述，包括關於我們的成長計畫、流動性和財務表現的陳述。這些都涉及風險和不確定性，實際結果可能與預期有重大差異。除法律另有規定外，我們不承擔更新這些聲明的義務。更多詳情請參閱我們最新的 10-K 表格和其他提交給美國證券交易委員會的文件中的「風險因素」部分。

We'll also reference non-GAAP financial measures like adjusted EBITDA and return on capital employed, which we believe are important indicators of operating performance because they exclude certain items that we do not believe directly reflect our core operations. Please see our earnings release for reconciliations to the most comparable GAAP measures. We hope you've had the chance to read our shareholder letter and look forward to your feedback. We'll begin with some brief prepared remarks from Fred and Salman, after their comments, we are going to be conducting an analyst interview with management.

我們也會參考非GAAP財務指標，如調整後的EBITDA和已動用資本回報率，我們認為這些指標是衡量經營績效的重要指標，因為它們剔除了我們認為不能直接反映我們核心業務的某些項目。請參閱我們的獲利報告，以了解與最接近的 GAAP 指標的調節情況。希望您已閱讀我們的股東信，期待您的回饋意見。首先，Fred 和 Salman 將發表一些簡短的準備好的演講。在他們講話之後，我們將對管理層進行分析師訪談。

Today's session will be conducted by Reggie Smith, analyst at JPMorgan. And with that out of the way, I'm going to turn the call over to Fred to kick things off. Fred?

今天的會議將由摩根大通分析師雷吉史密斯主持。既然如此，我就把電話交給弗雷德，讓他開始吧。弗雷德？

Thanks, Rob, and thank you all for joining us. This quarter, we continued to evolve MARA from a pure-play Bitcoin into a vertically integrated digital infrastructure company, one that converts energy into both value and intelligence. At the heart of our strategy is a simple belief, electrons are the new oil, energy is becoming the defining resource of the digital economy, powering everything from Bitcoin mining to artificial intelligence. And we believe those who control abundant, low-cost energy will shape the future of both finance and intelligence.

謝謝羅布，也謝謝各位的參與。本季度，我們繼續推動 MARA 從一家純粹的比特幣公司發展成為一家垂直整合的數位基礎設施公司，將能源轉化為價值和智慧。我們的策略核心是一個簡單的信念：電子是新的石油，能源正在成為數位經濟的決定性資源，為從比特幣挖礦到人工智慧的一切提供動力。我們相信，那些掌握豐富、低成本能源的人將塑造金融和情報的未來。

Bitcoin has now entered its institutional phase. We're seeing financial leaders such as BlackRock, Citi Corp and now even JPMorgan integrating Bitcoin into traditional frameworks. And we're seeing the establishment of strategic Bitcoin reserves by corporations and governments alike and even the -- Treasury has posted positive notes of up Bitcoin on X.

比特幣現在已經進入機構化階段。我們看到像貝萊德、花旗集團，甚至現在的摩根大通這樣的金融巨頭都在將比特幣整合到傳統框架中。我們看到企業和政府都在建立戰略性比特幣儲備，甚至財政部也發布了對比特幣的正面評論。

What miners have always understood is now being recognized by global markets, Bitcoin has Digital Energy, a mechanism for story and transmitting value. As one of the largest bitcoin miners in the world, MARA sits at the center of this shift. Our NP value infrastructure allows us to convert raw power directly to Bitcoin that we hold on our balance sheet, a distinct advantage that grounds our broader mission, transforming energy into intelligence.

礦工們一直以來所理解的，現在正被全球市場所認可：比特幣擁有數位能量，這是一種講述故事和傳遞價值的機制。身為全球最大的比特幣礦商之一，MARA 處於這項轉變的核心。我們的 NP 價值基礎設施使我們能夠將原始電力直接轉換為我們資產負債表上的比特幣，這是一個獨特的優勢，也是我們更廣泛的使命——將能源轉化為智慧——的基礎。

Every electron has potential value and artificial intelligence represents the next frontier events of the transformation of energy into even higher value. We believe that inference AI with the value of AI is actually created and drive and not treating in foundational models is where the industry will create the greatest amount of value over time.

每個電子都具有潛在價值，而人工智慧代表著將能量轉化為更高價值的下一個前沿領域。我們認為，人工智慧的價值在於推理，而推理才是人工智慧真正創造和驅動力，而不是在基礎模型中進行處理，這才是人工智慧產業隨著時間的推移創造最大價值的地方。

Every insight produced by an AI model has a cost per token, driven by the cost to build and operate the data center, of which the energy cost ticks up a major component. Over time, compute and the cost to build the data center will drop as technology advances such as HODL ASICs open-source models and the ability to operate in less sophisticated and less costly data centers drive efficiencies resulting in rapidly declining drops in cost per token, making the AI data today unable to compete on cost per token over time about significant technology refreshes, requiring even more and higher capital injections.

AI 模型產生的每項見解都有其每個代幣的成本，這主要取決於資料中心的建造和營運成本，其中能源成本是主要組成部分。隨著時間的推移，運算能力和資料中心建設成本將隨著 HODL ASIC 開源模型等技術的進步以及在不太複雜、成本更低的資料中心運行的能力而下降，從而提高效率，導致每個代幣的成本迅速下降，使得如今的 AI 資料在代幣成本方面無法與技術更新換代競爭，需要投入更多更高的資金。

We believe energy not compute really becomes the primary constraint on AI growth. We are already seeing the alternatives to GPUs enter the market and open source AI is making it far easier and much less expensive for companies to deploy advanced AI systems directly in their own private cloud environment.

我們認為，能源而非運算能力才是真正限制人工智慧發展的主要因素。我們已經看到 GPU 的替代方案進入市場，開源 AI 讓企業更容易、更經濟地在自己的私有雲環境中直接部署先進的 AI 系統。

In the past, most models were only available through public cloud APIs. That meant enterprises had to send data offsite and pay high per token fees to access AI capabilities. But today, many of the world's most capable models like LAMA straw and others are available in open source form, giving companies full control to run AI more cost efficiently and fine-tune their models privately.

過去，大多數模型只能透過公有雲 API 取得。這意味著企業必須將數據發送到異地，並支付高昂的代幣費用才能使用人工智慧功能。但如今，世界上許多最強大的模型，如 LAMA Straw 等，都以開源形式提供，使公司能夠完全控制人工智慧的運行，從而降低成本，並私下微調其模型。

This is a major inflection point for enterprise computing and the shift that plays directly to our strength as we build out low-cost, high-efficiency compute powered by our own energy infrastructure. we believe we're positioned to provide the kind of private, scalable environment enterprises need to deploy these open models securely.

這是企業運算領域的重要轉捩點，也是我們利用自身能源基礎設施建構低成本、高效率運算能力，進而發揮自身優勢的重大轉變。我們相信，我們有能力提供企業部署這些開放模式所需的私有化、可擴展環境。

MARA has positioned itself at the nexus of these two AI trends, open-source AI expanding the addressable market for private cloud compute. We believe that the future in structure will be able to serve that demand efficiently and profitably. This is where MARA's expertise in securing and operating low-cost power gives us a distinct advantage. Just as we optimize for the lowest cost per petahash and mining, we're now optimizing for the lowest cost per token in AI inference.

MARA 將自身定位在了這兩個 AI 趨勢的交匯點上：開源 AI 擴大了私有雲運算的潛在市場。我們相信，未來的建築結構將能夠有效率且獲利地滿足這項需求。MARA 在保障和營運低成本電力方面的專業知識使我們擁有明顯的優勢。正如我們優化每千萬億哈希運算和挖礦的成本一樣，我們現在也在優化人工智慧推理中每個代幣的成本。

Our long-term vision is to integrate these two energy pathways, Bitcoin and AI into a single platform. Bitcoin mining monetizes underutilized energy and stabilize grids, while AI inference transforms that same energy into intelligence and productivity. By bringing Bitcoin and AI together, we seek to maximize the value of every megawatt hour we manage.

我們的長期願景是將比特幣和人工智慧這兩種能源路徑整合到一個統一的平台中。比特幣挖礦將未充分利用的能源貨幣化並穩定電網，而人工智慧推理則將同樣的能源轉化為智慧和生產力。透過將比特幣和人工智慧結合起來，我們力求最大限度地發揮我們管理的每一兆瓦時的價值。

We've already begun executing on this strategy. This quarter, we installed our first AI inference rack at our Grand Berry site within a modular nonwater-cooled containerized data center. This site currently has 300 megawatts of nameplate capacity with potential opportunities to expand our growing AI inference business in combination with our Bitcoin mining operations at the site.

我們已經開始執行這項策略。本季度，我們在 Grand Berry 的模組化非水冷貨櫃式資料中心內安裝了我們的第一個 AI 推理機架。該網站目前擁有 300 兆瓦的額定容量，並有可能結合我們在該網站的比特幣挖礦業務，擴展我們不斷成長的 AI 推理業務。

This milestone marks a significant step forward in proving out our AI infrastructure and next-generation interim hypothesis. It also demonstrates the versatility of our platform, underscoring the potential flexibility of our mining sites to support AI workloads along with Bitcoin mining. Two major initiatives this quarter are propelling our strategy going forward.

這一里程碑標誌著我們在驗證人工智慧基礎設施和下一代中期假設方面邁出了重要一步。這也展現了我們平台的多功能性，突顯了我們的挖礦站點在支援人工智慧工作負載以及比特幣挖礦方面的潛在靈活性。本季兩項重大舉措將推動我們未來的策略發展。

First, our pending acquisition of Exaion, a subsidiary of EDF in France. Once regulatory approvals are completed and closing conditions have been met, Exaion will expand our capabilities through enterprise-grade, AI-optimized private cloud and HPC infrastructure. We believe this will position MARA as a credible -- for enterprises seeking secure localized inference capacity.

首先，我們正在進行對法國電力公司 (EDF) 子公司 Exaion 的收購。一旦監管部門批准完成，交易條件滿足，Exaion 將透過企業級、人工智慧優化的私有雲和高效能運算基礎設施來擴展我們的能力。我們相信這將使 MARA 成為企業尋求安全在地化推理能力的可靠選擇。

Second, today, we announced an initiative with MPLX, a separately traded public company formed by Marathon Petroleum Corporation the largest petroleum refinery operator in the United States to develop and operate multiple integrated power generation facilities and state-of-the-art data center campuses in West Texas.

其次，今天我們宣布與 MPLX 合作，MPLX 是由美國最大的煉油廠營運商 Marathon Petroleum Corporation 成立的一家獨立上市的公司，旨在西德克薩斯州開發和運營多個綜合發電設施和最先進的資料中心園區。

Under this initiative, MPLX will provide long-term access to lower-cost natural gas at scale where Mara will develop and operate on-site power generation and compute infrastructure. The initial capacity is expected to reach 400 megawatts with the option to expand to up to 1.5 gigawatts across three plant sites.

根據這項計劃，MPLX 將長期大規模提供低成本天然氣，Mara 將在此基礎上開發和營運現場發電和運算基礎設施。初期產能預計達到 400 兆瓦，並可選擇在三個電廠址擴建至 1.5 吉瓦。

We are also evaluating additional prospective sites to support modular AI and HPC data centers alongside mining operations, creating optionality future AI inference workloads. MARA's approach is to deploy smaller modular facilities directly at lower-cost power sites instead of building hyperscaler campuses. We believe this distributed model will enable us to capture value at the inference layer while continuing to monetize mining and grid sales.

我們也正在評估其他潛在地點，以支援模組化人工智慧和高效能運算資料中心以及採礦作業，為未來的人工智慧推理工作負載創造更多選擇。MARA 的做法是直接在成本較低的電力站點部署較小的模組化設施，而不是建造超大規模園區。我們相信，這種分散式模型將使我們能夠在推理層獲取價值，同時繼續透過挖礦和網格銷售來實現盈利。

This modular structure also gives more the optionality to shift capacity towards HPC over time. As an -- economics and infrastructure maturity support greater AI utilization. We believe MARA is positioned to capitalize on a key structural advantage as power becomes the primary key strength in AI growth.

這種模組化結構也提供了更多選擇，可以隨著時間的推移將容量轉移到高效能運算領域。隨著經濟和基礎設施的成熟，​​人工智慧的應用將得到更廣泛的支援。我們相信，隨著權力成為人工智慧成長的主要關鍵優勢，MARA 已做好充分準備，利用其關鍵的結構性優勢。

Together, Exaion and MPLX connect the two sides of our AI and data center business, energy and compute and strengthen our ability to control both cost and performance from power to inference. Internationally, we're deepening relationships across Europe and the Middle East, where we see significant opportunity to deploy our integrated energy and compute model.

Exaion 和 MPLX 攜手合作，將我們人工智慧和資料中心業務的兩個面向——能源和運算——連接起來，增強了我們從電力到推理的成本和效能控制能力。在國際上，我們正​​在深化與歐洲和中東的關係，我們看到了在這些地區部署我們一體化能源和運算模式的巨大機會。

Our pending Exaion acquisition exemplifies us, and we're honored to welcome Gerard Mestrallet, President Macron Special Energy Envoy, as an adviser tomorrow. His expertise strengthens our global strategy as we pursue our goal driving 50% of revenue from international operations by 2028.

我們即將完成的對 Exaion 的收購就是最好的例證，我們很榮幸地歡迎馬克宏總統能源特使 Gerard Mestrallet 明天擔任我們的顧問。他的專業知識增強了我們的全球策略，我們正朝著 2028 年實現 50% 的收入來自國際業務的目標邁進。

On the financial front, we continue to operate with discipline and transparency. We ended the quarter with 52,850 Bitcoin having mined over 2,100 BTC during Q3. We remain focused on improving free cash flow through ongoing cost optimization level efficiency gains and disciplined capital allocation. We have begun opportunistically monetizing Bitcoin from production to fund operating expenses and aim to limit reliance on our ATM to support growth initiatives, helping to mitigate shareholder dilution.

在財務方面，我們繼續秉持嚴謹透明的原則進行營運。第三季末，我們共持有 52,850 個比特幣，其中第三季挖出了超過 2,100 個比特幣。我們將繼續專注於透過持續的成本優化、效率提升和嚴格的資本配置來改善自由現金流。我們已開始抓住機會，利用生產過程中獲得的比特幣來籌集營運費用，並力求減少對 ATM 的依賴，以支持增長計劃，從而幫助減輕股東權益稀釋。

As I spoke about last quarter, Bitcoin prices have consolidated within a range of at least Q2. With intermittent volatility, we view this as a healthy period of equilibrium characterized by institutional inflows into ETF and balanced by long-term holder liquidation activity using [Dority Visitors] IPO analogy Bitcoin is going through an IPO where early investors in BCs are exiting and institutional investors are coming in forming a new base and foundation for growth.

正如我上個季度所說，比特幣價格至少在第二季以來一直在一個區間內盤整。儘管存在間歇性波動，但我們認為這是一個健康的平衡期，其特徵是機構資金流入 ETF，而長期持有者的清算活動與之平衡。 [Dority Visitors] IPO 類比比特幣正在經歷 IPO，早期投資者正在退出，而機構投資者正在進入，從而形成新的基礎和成長動力。

Meanwhile, broader macro trends, including rate cuts, and expanding liquidity suggest improving condition for risk assets. Regardless of short-term volatility, our long-term trajectory remains unchanged, building enduring value through energy ownership, operational excellence and strategic execution.

同時，包括降息和流動性擴張在內的更廣泛的宏觀趨勢表明，風險資產的狀況正在改善。無論短期波動如何，我們的長期發展軌跡保持不變，即透過能源所有權、卓越營運和策略執行來創造持久價值。

Finally, I want to provide an update on TPIC. While we continue to recognize the long-term potential of two-phase immersion, its practical broad application is still a few years out. And directorship cooling remains the preferred COO methodology of data center operators and compute OEMs.

最後，我想報告 TPIC 的最新進展。雖然我們繼續認識到兩相浸沒技術的長期潛力，但其實際廣泛應用仍需幾年時間。而管理層冷卻仍然是資料中心營運商和計算設備製造商首選的營運長方法。

We have exited near-term investment in two phase immersion to focus resources on opportunities with a more immediate and higher return potential. In closing, MARA is evolving from a Bitcoin miner into a digital infrastructure leader, combining energy generation, Bitcoin mining and AI compute under one scalable platform.

我們已停止對兩階段浸沒式結構的近期投資，以便將資源集中在更有直接回報潛力的機會。最後，MARA 正在從比特幣礦商轉型為數位基礎設施領導者，將能源生產、比特幣挖礦和人工智慧運算整合到一個可擴展的平台上。

Our guiding metric is simple profit per megawatt hour. It measures how effectively we convert energy into value, whether in Bitcoin, AI inference or grid stability. As we continue to execute, we believe the market will increasingly recognize the strength of this diversified model and the strategic importance of energy ownership in the digital economy. I want to thank our employees for their exceptional work this quarter and our shareholders for their continued support as we build Mara into the world's leading digital energy and infrastructure company.

我們的指導指標是每兆瓦時利潤。它衡量的是我們如何有效地將能量轉化為價值，無論是比特幣、人工智慧推理或電網穩定性。隨著我們不斷推進，我們相信市場將越來越認識到這種多元化模式的優勢以及能源所有權在數位經濟中的戰略重要性。我要感謝我們的員工在本季所做的傑出貢獻，以及我們的股東們在我們努力將 Mara 打造成世界領先的數位能源和基礎設施公司的過程中所給予的持續支持。

With that, I'll turn it over to Salman to review the financials.

接下來，我將把財務報表交給薩爾曼審核。

Thank you, Fred. During the quarter, global hash rate grew by roughly 20%, with the hash rate and network difficulty both hitting new all-time highs by end of the quarter. Bitcoin's price remained relatively range found, trading between $104,000 to $224,000, closing the quarter with a modest $7,000 gain. It was one of the most competitive mining environments in recent times and a difficult backdrop for our performance this quarter.

謝謝你，弗雷德。本季全球哈希率成長了約 20%，到本季末，哈希率和網路難度均創歷史新高。比特幣價格保持相對穩定的區間波動，在 104,000 美元至 224,000 美元之間交易，本季末小幅上漲 7,000 美元。這是近年來競爭最激烈的採礦環境之一，也是我們本季業績面臨的嚴峻挑戰。

Despite this, Q3 was the highest revenue and exahash quarter in the company's history. Our focus on operational and financial discipline over the past year is reflected in the substantial growth of our compute capacity and deploying holdings. Between Q3 2024 and 2025, our Bitcoin Holdings expanded by over 98%, growing from approximately 27,000 to nearly 53,000 bitcoin.

儘管如此，第三季仍是該公司歷史上營收和哈希率最高的季度。過去一年，我們對營運和財務紀律的重視體現在我們運算能力和部署資產的大幅成長。從 2024 年第三季到 2025 年第三季度，我們的比特幣持有量增加了 98% 以上，從大約 27,000 枚比特幣成長到近 53,000 枚比特幣。

Our energized hash rate also expanded, increasing 64% from 36.9% to 60.4 exahash per second. Bitcoin price appreciation resulted in approximately $4.3 billion or 256% increase year-over-year. While Fred spoke to our vision and strategy, our vertical integration and capital allocation strategy is reflective on our financial results.

我們的算力也得到了提升，從每秒 36.9% 提升至每秒 60.4 exahash，增幅達 64%。比特幣價格上漲導致其市值年增約 43 億美元，增幅達 256%。弗雷德談到了我們的願景和策略，而我們的垂直整​​合和資本配置策略則體現在我們的財務表現中。

That balanced execution allowed us to expand our holdings and take advantage of favorable market conditions, while maintaining liquidity and flexibility. We mined 2,144 Bitcoin and purchased an additional 2,257. The impact on our financials is evident in the results we achieved.

這種平衡的執行方式使我們能夠擴大持倉並利用有利的市場條件，同時保持流動性和靈活性。我們挖出了 2,144 個比特幣，並額外購買了 2,257 個。從我們所取得的業績可以看出，這對我們的財務狀況產生了明顯的影響。

Let's dig in. Revenues increased 92% to $252.4 million from $131.6 million in the third quarter of 2024. Bitcoin's average price increased 88% over that time period, which contributed $113.3 million. We mined an average of 23.3 BTC a day throughout Q3 compared to 22.5 BTC in Q3 of 2024 which resulted in 74 more bitcoin mined this quarter.

讓我們深入探討一下。2024 年第三季營收成長 92%，達到 2.524 億美元，上一季為 1.316 億美元。在此期間，比特幣的平均價格上漲了 88%，貢獻了 1.133 億美元。第三季我們平均每天挖到 23.3 個比特幣，而 2024 年第三季平均每天挖到 22.5 個比特幣，這意味著本季多挖到了 74 個比特幣。

Our strategy to deploy exahash responsibly resulted in growth of our BTC mine despite a significant growth in global hash rate and with network difficulty levels. We reported a net income of $123.1 million or $0.27 per diluted share last quarter compared to net loss of $124.8 million or negative $0.42 per diluted share in the third quarter of last year. We also booked a $343.1 million gain on digital assets, including Bitcoin receivable during the third quarter of 2025. The reflecting the positive impact of the Bitcoin holdings on our balance sheet.

儘管全球算力大幅成長，網路難度也隨之增加，但我們負責任地部署 exahash 的策略使我們的 BTC 礦場實現了成長。上季我們公佈淨利潤為 1.231 億美元，即每股攤薄收益 0.27 美元，而去年第三季淨虧損為 1.248 億美元，即每股攤薄虧損 0.42 美元。我們也確認了 2025 年第三季數位資產收益 3.431 億美元，其中包括比特幣應收款。這反映了比特幣持有量對我們資產負債表的正面影響。

Now let's talk about our cost structure. Our purchased energy cost to Bitcoin for the quarter was $39,235, and our daily cost per petahash per day improved 15% year-over-year, which we believe at scale is one of the lowest in the sector. This improvement is directly tied to our growing inventory of owned and operated sites, which now account for approximately 70% of our nameplate megawatt capacity.

現在我們來談談成本結構。本季我們購買比特幣的能源成本為 39,235 美元，每日每 petahash 的成本年減了 15%，我們認為，就規模而言，這是業內最低的成本之一。這項進步與我們不斷成長的自有和營運站點數量直接相關，這些站點目前約占我們額定兆瓦容量的 70%。

That transition supports our vertical integration strategy, but also pays dividends, both financially and operationally. Since we do not control the price of Bitcoin -- mine, minimizing the cost of inputs like energy are critical to the financial resilience and long-term success of the company.

這種轉型不僅支持我們的垂直整​​合策略，而且在財務和營運方面也帶來了回報。由於我們無法控制比特幣的價格——挖礦，因此最大限度地降低能源等投入成本對於公司的財務韌性和長期成功至關重要。

Next, I'll provide some insights into our Bitcoin Buildings and digital asset management strategy. MARA is the second largest corporate public holder of Bitcoin, and we seek to generate returns on our holdings as Bitcoin price appreciates. Our approach combines the potential for long-term discount appreciation with disciplined efforts to generate return while managing risk.

接下來，我將介紹我們的比特幣建築和數位資產管理策略。MARA 是第二大比特幣公眾持有者，我們希望隨著比特幣價格上漲而獲得收益。我們的方法結合了長期折價增值的潛力與在控制風險的同時創造回報的嚴謹努力。

Additionally, we have also used Bitcoin as a collateral to borrow under lines of credit. As of September 30, 2025, we held a total of 52,850 Bitcoin, including 17,357 Bitcoin that per loan actively managed and pledged as collateral. As such, approximately one-third of our total holdings were activated through our digital asset management strategy. In Q3, we issued $1.025 billion or $1.025 billion of 0 coupon convertible notes due 2032, extending our maturity profile and increasing balance sheet optionality.

此外，我們也曾使用比特幣作為抵押品來獲得信貸額度。截至 2025 年 9 月 30 日，我們共持有 52,850 枚比特幣，其中包括每筆貸款積極管理並作為抵押品的 17,357 枚比特幣。因此，我們透過數位資產管理策略啟動了約三分之一的總持股。第三季度，我們發行了 10.25 億美元或 10.25 億美元的 2032 年到期的零息可轉換債券，延長了我們的到期期限，並增加了資產負債表的選擇。

With additional liquidity, MARA gains strategic flexibility to act on opportunities, whether that's acquiring morbid coin, funding acquisitions balance sheet management or general corporate purposes. We have positioned MARA to act in response to market conditions in order to maximize long-term shareholder value. As of September 30, 2025, we held over $7 billion in liquid assets, giving us the flexibility to fund domestic growth and pursue international expansion.

有了額外的流動性，MARA 獲得了戰略靈活性，可以抓住各種機會，無論是收購 morbid 幣、為收購提供資金、資產負債表管理還是用於一般公司用途。我們已將 MARA 定位為可根據市場情況採取行動，以最大限度地提高股東的長期價值。截至 2025 年 9 月 30 日，我們擁有超過 70 億美元的流動資產，這使我們能夠靈活地為國內成長提供資金並進行國際擴張。

To streamline our communications starting in Q4, we will share our production on a quarterly basis. Investors can continue to monitor our monthly MARA pool production in real time on the manpool. As we have stated previously, electrons are the new oil, and we are laying the groundwork for 2026 and beyond. We're executing on a pipeline of energy infrastructure projects both in the US and internationally, and we expect these investments to expand our capabilities while keeping costs low.

為了簡化溝通，從第四季度開始，我們將按季度分享我們的生產。投資者可以透過 manpool 即時監控我們每月 MARA 池的產量。正如我們之前所說，電子是新的石油，我們正在為 2026 年及以後的發展奠定基礎。我們正在美國和國際上執行一系列能源基礎設施項目，我們期望這些投資能擴大我們的能力，同時保持低成本。

With that, I'll turn it over to Reggie Smith from JPMorgan. To begin our management interview. Reggie?

接下來，我將把麥克風交給摩根大通的雷吉‧史密斯。開始我們的管理階層面試。雷吉？

Good morning, guys. I appreciate you selected me for this call here. obviously very big announcements this morning. I guess kind of help me interpret this morning's announcement versus, I guess, kind of your prior strategy. Like what's being emphasized, deemphasized?

各位早安。感謝您選擇我參加這次電話會議。顯然，今天上午有很多重要消息要宣布。我想請您幫我解讀一下今天早上發布的公告，以及它與您之前的策略有何不同。例如，哪些方面被強調，哪些面向被弱化了？

Maybe talk about that from the -- like what's the most that you're placing on the business and maybe the lease because there's a lot going on here, certainly relative to the other Bitcoin miners, I know the other guys is either deploying mining or kind of colocation. You guys seem to have a lot more live mobile and maybe talk through those differences.

或許可以從這方面談談——比如你對這項業務投入的最大資金是多少，以及租賃情況，因為這裡有很多事情要處理，尤其是與其他比特幣礦工相比，我知道其他人要么在部署挖礦設備，要么在進行託管。你們似乎有很多行動端用戶，或許可以討論一下這些差異。

If you think about the deal we announced today, it's about getting access to low-cost energy that is reliable, available 24/7, because we are the generator, it provides us with a very low cost. If you look into the details of the announcement, you'll see that the pricing on the gas is amongst the lowest in the market.

如果你仔細想想我們今天宣布的這項協議，它關乎獲得低成本、可靠且全天候可用的能源，因為我們是發電方，所以成本非常低。如果你仔細查看公告的細節，你會發現天然氣的價格是市場上最低的之一。

The other thing is that it gives us now the capacity to add potentially up to 1.5 gigawatts of data center capacity if we want to -- which gives us lots of flexibility. A lot of our Bitcoin mining sites are very attractive to use for inference AI, as we discussed earlier. We talked about what we're doing at Granbury and what we'll be able to do at some of our other sites in a similar fashion where we can blend inference AI in Bitcoin mining.

另一方面，它使我們現在有能力根據需要增加高達 1.5 吉瓦的資料中心容量——這給了我們很大的靈活性。正如我們之前討論過的，我們的許多比特幣挖礦網站都非常適合用於推理人工智慧。我們討論了我們在格蘭伯里正在做的事情，以及我們將在其他一些站點以類似的方式做的事情，即把推理人工智慧融入比特幣挖礦中。

But the relationship with MPLX and the opportunities it provides give us a much broader canvas that we can paint on, whether that is traditional HPC, like some of our peers have done or whether we want to build it out as hybrid AI, inference AI and Bitcoin mining sites. So it gives us a lot of flexibility. And we believe controlling and owning power is the core part of any company that operates in the digital infrastructure space.

但與 MPLX 的合作關係以及它所提供的機會，為我們提供了一個更廣闊的創作空間，無論是像我們的一些同行那樣發展傳統的高效能運算，還是將其建構成混合人工智慧、推理人工智慧和比特幣挖礦網站。所以它給了我們很大的彈性。我們認為，控制和擁有權力是任何在數位基礎設施領域運作的公司的核心組成部分。

When you look at the spending that's going on. And I think Sachin Ardell said this in a recent podcast that was quoted where he was quoted as saying that compute isn't the constraint, energy is the constraint. And so access to energy, we believe, is critical. We think inference over the long term is where all the value is going to get created in this space.

當你審視一下目前的支出狀況。我認為 Sachin Ardell 在最近的一個播客節目中說過類似的話，他當時說，計算能力不是瓶頸，能源才是瓶頸。因此，我們認為，獲得能源至關重要。我們認為，從長遠來看，推理才是這個領域所有價值的創造所在。

But we believe that Bitcoin mining has a very important role to play in which is balancing grids, but providing a flexible load when mixed with AI, such that AI can begin to operate in more places than it does today. And the last thing I'd say is that we believe that the technology curve is going to move so quickly in this space. Because you have to realize that just like in Bitcoin mining, where cost per petahash is the most important metric that drives profitability in the AI business, unless you are in the application layer.

但我們相信，比特幣挖礦在平衡電網方面發揮著非常重要的作用，當與人工智慧結合時，可以提供靈活的負載，使人工智慧能夠在比現在更多的地方運作。最後我想說的是，我們認為這個領域的技術發展速度將會非常快。因為你必須意識到，就像比特幣挖礦一樣，每千萬億哈希成本是人工智慧業務獲利能力的最重要指標，除非你身處應用層。

In other words, running -- owning the data and the application that is generating value for the enterprise in health care, owning the health care data, running the actual analysis. The only thing hosting providers and model operators provide our tokens in the sense of we need lowest cost per token if we're going to use that service.

換句話說，營運——擁有為醫療保健企業創造價值的數據和應用程序，擁有醫療保健數據，並進行實際分析。託管服務提供者和模型運營商提供的唯一條件是，如果我們要使用該服務，就需要最低的代幣成本。

And using the APIs when the cloud providers is a very expensive way of running AI and most enterprises today are being confronted with the fact that the cost per token is too high using existing systems, and they want to move to lower-cost systems, and we're going to start seeing that we already are seeing ASIC-based solutions coming open source models, all of which will allow enterprises to build their own and operate their own private cloud or use those services from third parties, allowing them to drive value from AI.

使用雲端供應商的 API 運行 AI 是一種非常昂貴的方式，如今大多數企業都面臨著這樣一個事實：使用現有系統，每個代幣的成本太高，他們希望轉向成本更低的系統。我們將開始看到，基於 ASIC 的解決方案已經出現在開源模型中，所有這些都將允許企業建立和營運自己的私有雲，或使用第三方服務，使他們能夠從 AI 中創造價值。

So I think for a lot of the big guys, the challenge is they are doing deals with colocation partners where they are not taking on the debt. The debt is being laid on the joint venture or the SPV related to that colocation facility. And that correlation partners having to deploy a lot of capital to build the sites and equip those sites and you have technology obsolescence over the course of a 10-year lease, you will have to upgrade the hardware in that location.

所以我認為，對於許多大公司來說，挑戰在於他們與託管合作夥伴達成的交易中，他們並沒有承擔債務。該債務由與該託管設施相關的合資企業或特殊目的公司承擔。而相關合作夥伴必須投入大量資金來建造站點並配備這些站點，而且在 10 年的租賃期內，技術會過時，因此您必須升級該地點的硬體。

And you have to estimate that in the cost of where it's going to be to build and operate. And I think there's a risk potentially, that $1.4 trillion of data center contracts signed by OpenAI over the -- that will have to be operating in the next five years according to what was recently reported in the press, that some of that may not actually be able to come online and generate revenue.

你必須把這些成本估算到建造和營運成本。我認為存在一個潛在風險，OpenAI 簽署的價值 1.4 兆美元的資料中心合約——根據最近媒體的報道，這些資料中心必須在未來五年內投入營運——其中一些可能實際上無法上線並產生收入。

So I think our approach is much better, more prudent, certainly much more capital efficient. And by being at the end of the spectrum where we're vertically integrated and able to operate at lowest cost per token and deliver lowest cost per token, we will have a significant advantage in the marketplace.

所以我認為我們的方法好得多，更謹慎，當然也更有資本效率。憑藉我們在垂直整合領域的領先地位，我們能夠以最低的代幣成本運作並提供最低的代幣成本，我們將在市場上擁有顯著優勢。

And Reggie, just a reminder, we -- today, we control approximately 2 gigawatts of capacity. And this added capacity is incremental to that, that takes us to close to 3.5 gigawatts over a period of time.

雷吉，提醒你一下，我們——今天，我們控制著大約 2 吉瓦的發電容量。而新增的這些容量是在此基礎上逐步增加的，這樣一來，一段時間後我們的總容量將接近 3.5 吉瓦。

Got it. Understood. I'd like -- I appreciate the color there, and I was doing some kind of light math this morning. And when I think about, I guess, kind of AI and HPC, you made a comment in your shareholder letter about the price of power and the price to compute. You made some parallels between Bitcoin mining and HPC. And I was looking at the numbers, and I think they may be a little bit off, but directionally, this is like a fair statement.

知道了。明白了。我喜歡——我很欣賞那裡的顏色，而且我今天早上還做了一些簡單的數學運算。當我思考人工智慧和高效能運算時，你在致股東的信中談到了電力價格和運算成本。你把比特幣挖礦和高效能運算做了一些類比。我查看了這些數據，我認為它們可能有點偏差，但從方向上看，這算是一個合理的說法。

When you look at Bitcoin Mining, the price of power and the price of the actual ASICs, you think about depreciating per hour are about the same, like a 1:1 ratio there. For GPUs, that ratio is more like 1 per 10 GPU, some depreciation charge and not really depreciation is super high. So you talked about ASICs and somehow, I guess, driving the cost of the hardware, am I thinking about that right, like what are you seeing and kind of where do you see the role going there?

當你觀察比特幣挖礦時，你會發現電力價格和ASIC礦機的價格，以小時折舊計算，兩者大致相同，比例約為1:1。對於 GPU 而言，這個比例更像是每 10 個 GPU 中有一個，其中包含一些折舊費用，但實際上折舊費用非常高。所以你談到了ASIC晶片，我想，這在某種程度上推高了硬體成本，我的理解對嗎？你看到了什麼？你認為ASIC晶片的發展方向是什麼？

Just think about it this way. When Bitcoin mining started, we were running CPUs, right? Then we went to GPUs, then we went to FPGAs, then we went to ASICs. And when you look at the amount of compute power, for -- think of it as the number of terahash we could produce for a jewel of energy. It has dramatically changed, so you are now processing many more calculations at much lower cost of energy.

換個角度想。比特幣挖礦剛開始的時候，我們用的是CPU，對吧？然後我們轉向了GPU，然後轉向了FPGA，然後轉向了ASIC。當你審視計算能力時，可以把它想像成我們用一小塊能量可以產生的哈希運算次數（以太哈希為單位）。它發生了巨大的變化，因此您現在可以以更低的能源成本處理更多的計算。

And in our business, we depreciate the compute over three years. So if you're a hyperscaler and you're signing a deal for 10 years, some of these are 15 years and the depreciation schedule is five years for the machines. Does that mean they're going to have to replace those machines 3 times in that cycle, right? And to your point, GPUs to power is most probably a 10:1 ratio.

在我們的業務中，我們對計算機進行三年折舊。因此，如果您是一家超大規模資料中心運營商，並且您簽訂了一份為期 10 年的合同，其中一些合同的期限為 15 年，而機器的折舊計劃是五年。那是不是代表他們在這個週期內要更換這幾台機器3次？如你所說，GPU 與電源的比例很可能是 10:1。

And as you get to ASIC, that starts dropping and power starts becoming an even more important component. And when you start looking at the end cost per token, at that point, the model cost also comes into play. And so if you have open source models, if you have low-cost hardware, that's energy efficient, you're operating in data centers that don't cost you $10 million of megawatt to build. You start getting to economics, would start resembling Bitcoin mining overturns.

而到了ASIC晶片時代，功耗就開始下降，成為更重要的因素。當你開始考慮每個代幣的最終成本時，模型成本也會發揮作用。因此，如果你擁有開源模型，如果你擁有低成本、節能的硬件，那麼你就可以運營那些建設成本不超過每兆瓦 1000 萬美元的數據中心。當你開始談到經濟學時，你會發現它與比特幣挖礦的顛覆性變革非常相似。

Understood. Now help me understand this. I want to understand or make sure I'm hearing you correctly. When you think about kind of the investment risk and the CapEx risk within the chain. Obviously, you've got guys that are building data centers, you've got people that are buying like GPUs and hardware and then you say, obviously, you got the model guys as well.

明白了。現在請幫我理解一下。我想確認一下我是否聽懂了你的意思。當你考慮到整個產業鏈中的投資風險和資本支出風險。顯然，有人在建造資料中心，有人在購買GPU和硬件，然後，顯然，也有模型製作者。

I guess your comments on kind of where the CapEx risk is greatest. Are you suggesting that the people that are buying the machines are taking on the most risk? Or do you think there's still substantial risk in building big dissenters. And I ask you that in the context of you guys just, I guess, bought a few GPUs yourself, like help me square all of this together to understand kind of what your view is there?

我想你指的是資本支出風險最大的部分。你是說購買這些機器的人承擔了最大的風險嗎？或者你認為培養強大的反對派仍然存在相當大的風險嗎？我想問的是，鑑於你們自己也買了一些顯示卡，能否幫我把所有這些資訊整理一下，讓我了解你們的看法？

Right. So part of the question is, are you in the business of being a bare metal shop, right? You're providing essentially hosting and GPUs. Looking at what iron is doing, right? Bare metal, somebody has to load their software on it, but they're renting capacity on GPUs effectively.

正確的。所以問題的一部分是，你們的業務是做裸金屬加工嗎？你主要提供的是主機和GPU。看看鐵的作用，對吧？裸機上需要有人載入軟體，但實際上他們正在租用 GPU 的運算能力。

And that deep cloud as it's called, that case, the owner operator is funding the GP purchases, right? In the case of a colocation, there are some deals that have been done where the operator is funding the GPUs and there are other deals where the lesser of the space, if you would, is bringing the GPUs, and they are the buyer and operator.

而對於這種被稱為「深層雲」的情況，所有者運營商正在為GP的購買提供資金，對嗎？在託管環境中，有些交易是由營運商出資購買 GPU，而有些交易則是空間較小的一方（如果可以這麼說的話）提供 GPU，他們既是買家又是營運商。

So if Microsoft comes and is going to contract with you to just buy capacity from you, they're going to bring the GPU, so far, you would hope at least, and they're taking that risk. But there are lots of different models out there being operated by people. What we're doing with inference at the edge is much more around providing inference AI, which is not running on GPUs. We're running on ASIC type solutions.

所以，如果微軟來和你簽訂合同，只購買你的產能，他們至少會提供GPU，至少目前來看是這樣，他們也承擔這樣的風險。但市面上有許多不同型號的模型在由人們操作。我們在邊緣進行推理更多的是為了提供推理 AI，而推理 AI 並不是在 GPU 上運行的。我們採用的是ASIC類型的解。

And so it's a very -- it's a different model from a hardware cost perspective. It's air cooled that's not liquid cold, for example, which means your infrastructure is much less expensive. You're not having to spend many millions of dollars per megawatt on building infrastructure, specialized cooling infrastructure. And all of that adds up to the economics of what you can do.

因此，從硬體成本的角度來看，這是一個非常不同的模型。例如，它是風冷式的，而不是液冷式的，這意味著您的基礎設施成本要低得多。你不需要花費數百萬美元/兆瓦的資金來建造基礎設施和專門的冷卻基礎設施。所有這些因素加起來，就決定了你能做什麼。

But inference is also done at smaller volumes, right? You don't have to do 100-megawatt sites yet. Most of the needs for inference still are quite young. It's early in the market. But if you believe what Gartner and the Analyst Day, over the next three to five years, the inference will be the primary generator of revenues and value creation within the AI space. So that's where we're swimming.

但是，在較小樣本量的情況下也可以進行推理，對吧？你現在還不需要建造100兆瓦的電站。大多數推理需求仍處於發展初期。現在還是市場初期。但如果你相信 Gartner 和分析師日的預測，那麼在未來三到五年內，推理將成為人工智慧領域收入和價值創造的主要來源。所以，這就是我們現在游泳的地方。

Understood. You've got to skip around a little bit here. I wanted to talk about Exaion, I think kind of looked back into the broader discussion. But obviously, you guys have enough set of acquisition. Help what they do today? Maybe talk about the scale of their operations, like are they running data centers today? And if so, what's the size of those what do they do exactly?

明白了。這裡需要稍微跳著來。我想談談 Exaion，我覺得這有點像是在回顧更廣泛的討論。但很顯然，你們已經擁有足夠的收購資源。幫助他們完成今天的工作？或許可以談談他們的營運規模，例如他們現在是否經營資料中心？如果屬實，它們的尺寸是多少？它們的具體作用是什麼？

Yes. Exaion is today until we close a full subsidiary of EGF that operates EDF data centers were all of the data for the nuclear fleet operates in this process. So they run EDF AI and traditional data centers across the EDF enterprise. They have about four data centers today, three in France, one in Canada.

是的。Exaion 目前是 EGF 的全資子公司，負責營運 EDF 資料中心，核動力艦隊的所有資料都在此過程中運作。因此，他們為整個 EDF 企業經營 EDF AI 和傳統資料中心。他們目前擁有大約四個資料中心，其中三個在法國，一個在加拿大。

They also operate quantum technology in the Canadian data center, which is made available for research purposes, and they have built a whole set of software solutions that allow you to operate the data center, store data in full private mode, meaning the user's data fully encrypted. Exaion doesn't have the keys to that data. And so we're that data center to be broken into, if you say, of somebody were to steal data, the data in the data center is encrypted. So the customer holds the key to that data.

他們還在加拿大數據中心運行量子技術，該數據中心可供研究使用，並且他們構建了一整套軟體解決方案，使用戶能夠操作數據中心，以完全私密模式存儲數據，這意味著用戶的數據將完全加密。Exaion沒有取得這些資料的金鑰。所以，即使有人試圖入侵我們的資料中心竊取數據，資料中心內的資料也是加密的。所以，客戶掌握著取得這些數據的關鍵。

And so it's a way to build private cloud solutions that are fully secure. And so the whole reason for making investment in Exaion is it gives us access to a team and an existing set of data centers that are Tier 3 and Tier 4 already. They know how to operate the most sensitive data, data to protect it. They have existing customers. So they have experience and we are going to leverage their knowledge, their experience, their technology and their platforms to expand what they do on a global basis.

因此，這是一種建構完全安全的私有雲解決方案的方法。因此，我們投資 Exaion 的全部原因在於，它使我們能夠接觸到一支團隊和一套現有的 Tier 3 和 Tier 4 資料中心。他們知道如何處理最敏感的數據，以及如何保護這些數據。他們擁有現有客戶。所以他們擁有豐富的經驗，我們將運用他們的知識、經驗、技術和平台，在全球擴展他們的業務。

Got it. So they're asset like. They're more of a service layer, they're engineers or software, things like that, like they don't actually own any data centers. It's really running that data center securing data, is that the right way --

知道了。所以它們就像資產一樣。他們更像是服務層，他們是工程師或軟體工程師之類的，他們實際上並不擁有任何資料中心。它確實在運行那個數據中心來保護數據，這樣做對嗎？--

Yes.

是的。

Understood. Okay. Is there a way to frame it maybe early their revenue run rate? And interestingly, about that transaction, I think the first transaction, you bought them for $168 million. The next 11% will be at a much higher rate. Like what was the thinking there --

明白了。好的。有沒有辦法提前說明他們的營收成長率？有趣的是，關於那筆交易，我認為第一次交易，你以 1.68 億美元的價格買下了它們。接下來的11%將以更高的速度成長。他們當時到底是怎麼想的？--

I think you can think of how many times deals like this are structured, you're paying for a portion of the business based on where it is today? And then the growth opportunity for the existing investors is in executing on a plan to help grow the business and therefore, you're going to pay a higher multiple for that. That's how you should think --

我想你可以想想，像這樣的交易有多少次都是這樣，你根據公司目前的狀況支付一部分費用？而對於現有投資者來說，成長機會在於執行一項幫助企業發展的計劃，因此，你需要為此支付更高的倍數。你應該這樣想。--

Okay. Now on the tile. So the MPLX transaction, real quick on that, does it require any like ERCOT approval like these guys have the natural gas, you guys would make the power plant or from the generation assets and the data center but is anything needed from ERCOT? Any roadblocks there? And how quickly could you -- data center up in kind of running?

好的。現在開始鋪磁磚。關於MPLX交易，我簡單問一下，它是否需要像ERCOT這樣的機構的批准？例如，他們有天然氣，你們會利用發電資產和資料中心來建造發電廠，但是否需要ERCOT的任何批准？那邊有什麼障礙嗎？你能多快讓資料中心恢復運作？

Yes. I think you have to think of it more as the first thing we're doing is building a power generating station, which will be gas-fired power plant. So you have regulatory requirements around air permits, for example, which in the current political environment should not be exceedingly difficult to acquire. We feel fairly confident that we'll be able to get those without much problem.

是的。我認為你應該把它看作是我們首先要做的事情是建造一座發電站，這將是一座燃氣發電廠。例如，在航空許可證方面有一些監管要求，但在目前的政治環境下，取得這些許可證應該不會太難。我們相當有信心能夠順利拿到這些東西。

So once you build a power plant, then because you are not directly bird attached yet you then have to apply to attach to the grid and be a provider to the grid. So there's a regulatory process for that. Meanwhile, you can be producing energy and operating data center fully behind meter. And it's -- ERCOT gets involved when you connect to the grid or the utility stuff. When you connect to the grid.

所以，一旦你建好了發電廠，因為你還沒有直接併入電網，那麼你就必須申請併入電網，成為電網的供電者。所以這方面有相應的監管流程。同時，您可以完全在電錶後生產能源並營運資料中心。而且，當你連接到電網或公用設施時，ERCOT 就會介入。當你連接到電網時。

And the goal here, what's really important to remember about this MPLX relationship is it gives us the ability to own and operate gas-fired power plants with very low cost gas with the ability to colocate large-scale data centers with reliable 24/7 power is a very attractive part of the marketplace. And so it gives us a lot of control to really drive our growth in a very cost-effective way. And I think it positions us very well come what may in this HPC AI market and give us a lot of opportunities. to really operate and continue to generate a lot of value for our shareholders.

而我們與 MPLX 建立的這種關係，真正重要的是要記住，它使我們能夠以非常低的成本擁有和運營燃氣發電廠，同時還能將大型數據中心與可靠的 24/7 全天候電力連接在一起，這在市場上極具吸引力。因此，這讓我們能夠以非常經濟高效的方式真正掌控並推動我們的成長。我認為無論未來如何，這都使我們在高效能運算人工智慧市場中處於非常有利的地位，並為我們提供了許多機會，讓我們能夠真正運作並繼續為股東創造巨大價值。

No, I agree. It's been thinking about this idea of like vertical integration, and I didn't know if it was going to be a tower company acquiring data center capabilities and the other around. So this is very interesting. If I could dig in a little bit more. So I think you talked about [400] megawatts of capacity to start.

不，我同意。我一直在思考垂直整合的想法，但我不知道這是否意味著一家鐵塔公司收購資料中心能力，或其他類似的情況。這很有意思。如果我能再深入挖掘一下就好了。所以我想你之前提到過，最初的裝置容量是 400 兆瓦。

Should we think about like the minimum effective dose kind of get started. So I don't know if you want to commit to 400 megawatts were out the bad, is it at -- megawatts and how quickly can set like this come together? And then I know it's early days, but like we've heard estimates of up to $10 million per megawatt to build out a data center, like what are you thinking about from that perspective as well?

我們是不是應該考慮最小有效劑量之類的東西？所以我不知道你是否願意投入 400 兆瓦，如果情況糟糕的話，它是否達到 - 兆瓦，以及這樣的專案能以多快的速度完成？我知道現在下結論還為時過早，但我們聽說建造一個資料中心每兆瓦的成本估計高達 1000 萬美元，從這個角度來看，您對此有何看法？

So you don't build a power plant in 20-megawatt increment. You build it right to a certain size at each site. So there are three sites will likely think of it in 100-megawatt increments initially, but you have the ability to scale these plants, much larger. As it relates to the data centers, we have the optionality. We can build these as traditional Bitcoin mining data centers that are fully containerized at somewhere around $1 million including hardware costs for compute.

所以你不會以 20 兆瓦為增量來建造發電廠。每個工地都依照特定尺寸建造。因此，最初可能會以 100 兆瓦為增量考慮這三個地點，但你有能力將這些工廠擴大到更大的規模。就資料中心而言，我們有選擇權。我們可以將這些建構成傳統的比特幣挖礦資料中心，完全採用容器化設計，成本約為 100 萬美元，其中包括計算硬體成本。

If you then want to look at going the AI route, if we're doing it similar to how we're running the inference AI, we're running today, the actual infrastructure cost is very similar. It may be on a little bit more expensive, depending on the cooling technology, if we use direct-to-chip cooling or we continue to use air cooler. And if you use direct-to-ship cooling, your cost of infrastructure will end up somewhat higher.

如果你接下來想考慮採用人工智慧路線，如果我們採用與我們目前運行推理人工智慧類似的方式，那麼實際的基礎設施成本非常相似。根據冷卻技術的不同，如果採用晶片直接冷卻或繼續使用空氣冷卻，成本可能會稍微高一些。如果採用直接對運冷卻，基礎設施成本最終會略高一些。

But the key is we're not building buildings that take three years to build. We're doing these as modular container solutions, which gives us full flexibility to reconfigure a site depending on whatever we want to do at it. And I'm a big believer that you will see very high-performing HPC capable modular solutions on the marketplace within the next two, three years, where you will be able to deploy the same sophisticated solutions you're building in these very sophisticated data centers, where people can run some of the most sophisticated they need to.

但關鍵在於，我們建造的不是那種需要三年才能建造的建築。我們採用模組化容器解決方案，這使我們能夠根據想要在站點上執行的任何操作，靈活地重新配置站點。我堅信，在未來兩三年內，市場上將會出現效能卓越的高效能運算模組化解決方案，屆時，人們可以在這些高度複雜的資料中心部署與建置的相同複雜解決方案，從而運行他們需要的一些最複雜的程式。

Remember, there are not many customers in the world who need data centers of the scale that open AI needs it, right? OpenAI needs a lot of compute capacity because of the breadth of data and the breadth of solutions their models operate. If you remember what DeepSeek did and how deep sea create the turn in the market, it's because instead operating with a broad foundational model, they only load into memory, specifically the model segments that they need and the data to solve the query, which means you now don't need all of that scale.

請記住，世界上並沒有多少客戶需要像開放式人工智慧所需的那種規模的資料中心，對吧？OpenAI 需要大量的運算能力，因為其模型處理的資料量龐大，且所處理的解決方案範圍廣泛。如果你還記得 DeepSeek 的所作所為以及深海數據如何改變了市場格局，那是因為他們沒有採用廣泛的基礎模型，而是只將所需的模型片段和解決查詢所需的數據加載到內存中，這意味著你現在不再需要那麼大的規模。

So what I think will happen in the marketplace is that you're going to have efficiencies and models going to open source, clients developing their own models and training their own models because the clients don't want to give the data to OpenAI. And I'll give you an example. I was at FI last week in Saudi Arabia, and I was sitting with the Head of Strategy for Aramco on a panel. And they don't put their seismic data in the cloud. They're not going to do that. What do they do?

所以我認為市場上將會出現的情況是，效率會提高，模型會開源，客戶會開發自己的模型並訓練自己的模型，因為客戶不想把資料交給 OpenAI。我給你舉個例子。上週我在沙烏地阿拉伯參加了FI大會，並和沙烏地阿美公司的策略主管一起參加了一個小組討論。他們並沒有將地震資料上傳到雲端。他們不會那樣做的。他們是做什麼的？

They build their own models. Other companies do the same thing. Look at what Lockheed just did the deal the -- with Google right? It's an on-prem solution. You are not -- I'm not going to put my data up into your cloud, Google. You're going to build a cloud instance on-prem, on my site that is airgap from your systems.

他們自行搭建模型。其他公司也這樣做。看看洛克希德馬丁剛剛和谷歌達成的交易，對吧？這是一個本地部署解決方案。你不行－我不會把我的資料放到你的雲端，Google。你將在我這裡搭建一個本地雲端實例，該實例與你的系統完全隔離。

That's what corporations want. They want data sovereignty. They want private cloud. They don't want to run up in Meta's cloud, Amazon's cloud or open AI systems. 70% of corporate days today is still not in the cloud. There's a reason for that. And I think when you look at inference, inference is driving insights from the data that runs your company, right?

這正是企業所希望的。他們想要資料主權。他們想要私有雲。他們不想使用Meta的雲端、亞馬遜的雲端或開放式AI系統。如今，企業70%的工作日仍不在雲端。這其中是有原因的。我認為，當你審視推理時，推理就是從公司運作所需的數據中挖掘洞察，對嗎？

If you're in the health care business, doing drug discovery, it's all the patient data, the lab samples, et cetera, all that data you're driving insights from it, right? And if you are doing building airplanes, it's all the design data and the manufacturing data. If you're running a factory, it's the operations data of the factory, right? If you're running a power plant, it's the operations data of that power plant. You don't want to run that off site.

如果你從事醫療保健行業，進行藥物研發，那麼所有的病人數據、實驗室樣本等等，所有這些數據都能為你提供洞見，對吧？如果你從事飛機製造，那就需要所有的設計數據和製造數據。如果你經營工廠，那指的是工廠的營運數據，對吧？如果你經營一座發電廠，那麼它就是該發電廠的運作數據。你不想把程式部署到異地。

You want to actually run it on site because as those systems become mission-critical and actually operate the resources and operate parts of the business, you can't take the risk that you have a system failure that brings your whole business down just because you lose a lead to a cloud or Amazon goes offline like it did the other day.

你希望它能在本地運行，因為隨著這些系統變得至關重要，並實際運行資源和部分業務，你不能冒著系統故障導致整個業務癱瘓的風險，僅僅因為你丟失了一個雲端線索或者像前幾天那樣亞馬遜離線了。

So I think people really have to understand that there is a limit to what data and how much risk people want to do in putting their core critical assets into a cloud operated by a third-party. And if they can solve the model issue and do it at lower cost, near prem or on-prem in a private environment, they will do it.

所以我認為人們真的需要明白，將核心關鍵資產放到第三方營運的雲端，其資料量和風險承受能力都是有限的。如果他們能夠解決模型問題，並且以更低的成本在私有環境中實現近本地部署或本地部署，他們就會這樣做。

And I have been speaking with the heads of AI for major corporations in the financial market today, who tell me that they are relocating AI systems out of the cloud back to near-prime on-prem private solutions because it is significantly less expensive to operate than doing it in an Amazon cloud or other places like that.

今天，我與金融市場主要企業的 AI 負責人進行了交談，他們告訴我，他們正在將 AI 系統從雲端遷移回接近主伺服器的本地私有解決方案，因為與在亞馬遜雲端或其他類似地方運作相比，本地私有解決方案的營運成本要低得多。

And I think that the analyst community really needs to do a much better job of talking to the enterprises who are the users, these are the people who are actually going to pay the money that will allow open AI to be successful or not, that will allow Microsoft to be successful or not. You can talk to your blue interface with the people building these things, but it's like building railways. If there isn't passenger traffic and there is any cargo, the rail line fail. So that'd be down on this, but this is an important thing that a lot of people aren't doing. You need to talk to the customers, who's going to pay for this stuff.

我認為分析師群真的需要更好地與企業用戶溝通，這些人才是真正會花錢的人，他們的付出將決定開放人工智慧能否成功，微軟能否成功。你可以透過藍色介面與建造這些東西的人交談，但這就像修建鐵路一樣。如果沒有客運，而又有貨物運輸，鐵路就會癱瘓。所以這方面做得不好，但這是一件很多人都沒做到的重要事。你需要和顧客談談，畢竟誰來為這些東西買單。

And I want to make sure I'm hearing this right and connect these debts. So I think you mentioned kind of a smaller kind of, I think, a 1 megawatt -- what do you call it, I guess, kind of like a sample or a small -- data center. If I'm hearing this right, are you saying that like that could become like the prototype for enterprises having their own on-premise like AI --

我想確認一下我是否聽對了，並把這些債務連結起來。所以我想你提到了一個規模較小的，我想，一個1兆瓦的——該怎麼稱呼它呢，我想，有點像一個小型資料中心。如果我理解沒錯，你的意思是說，這可以成為企業擁有自己的本地人工智慧系統的原型嗎？

Yes. So think of it this way, right. Give you an oil drilling example, right? So you have an exploration drill that's drilling, you have seismic data. Today, you have to plan exactly the drill profile and what some -- what the drill operator is going to do. And so the oil companies have built these very sophisticated AI models that run in a module container typically out on the drilling side that are collecting real-time data from the drill and then feeding back instructions into to the drill master. That's an existing example.

是的。所以你可以這樣想，對吧。舉個石油鑽探的例子，好嗎？所以，你們有一台正在鑽探的探勘鑽孔機，你們有地震資料。如今，你必須精確地規劃鑽孔剖面以及鑽機操作員將要進行的操作。因此，石油公司建立了非常複雜的人工智慧模型，這些模型通常在鑽井平台的模組容器中運行，從鑽機收集即時數據，然後將指令回饋給鑽井主管。這是一個現成的例子。

You can go to a trading, a financial trading company. And their whole thing is speeding latency. They want their systems operating on their local network, not on a wide area of connection where there's latency because 25 millisecond delay in a response means they lose the profit on a trade.

你可以去交易公司，或是金融交易公司。他們所做的一切都是為了降低延遲。他們希望自己的系統在本地網路上運行，而不是在有延遲的廣闊連接區域上運行，因為 25 毫秒的響應延遲意味著他們在交易中會損失利潤。

And so there are -- whether you're looking at defense, which is going to be a huge growing sector when it comes to AI, just look at the amount of AI that's needed to operate in any third of war today. Look at health care, look at manufacturing and production, look at the movie television industry, the single largest consumer of tokens in AI are video illustrations and audio generation. Those are the systems that consume that these diffusion models are the single largest consumer of tokens.

因此，無論是從國防領域來看，人工智慧都將是一個巨大的成長領域，看看如今任何三分之一的戰爭都需要多少人工智慧就知道了。看看醫療保健行業，看看製造業和生產行業，看看電影電視行業，人工智慧領域代幣的最大單一消費領域是視訊插圖和音訊生成。這些系統消耗代幣，因此這些擴散模型是代幣的最大單一消耗者。

And so cost per token is very critical to them because if you're going to generate a 5-, 10-, 15-minute clip of video, it takes multiple factors in magnitude, more tokens than asking OpenAI where your feed your lunch today.

因此，每個代幣的成本對他們來說非常關鍵，因為如果你要產生一段 5 分鐘、10 分鐘、15 分鐘的影片片段，所需的代幣數量是詢問 OpenAI 你今天在哪裡吃午餐的數倍。

And so I think, again, the marketplace gets all hyped up about these big contracts, but they really need to look at who's actually going to use this stuff? What are they going to use it for? What can they afford to pay for it? Will the pricing trends be over time and to use the worn-out win rest technology, if you're in our business, you want to be skating to where the puck is going to be, right? You don't want to be chasing the puck. And I think there are a lot of people announcing deals out there getting on the bandwagon to pump their stock when they need to look at what's this industry going to look like in five years.

所以我覺得，市場對這些大合約反應過度，但他們真的需要看看誰會真正使用這些東西？他們打算用它做什麼？他們能負擔得起多少錢？價格趨勢會隨著時間的推移而改變嗎？如果採用這種過時的勝利休息技術，如果你從事我們這個行業，你肯定希望滑到冰球將要到達的地方，對吧？你不想一直追著冰球跑。我認為現在很多人都在宣佈各種交易，只是為了搭上順風車來提振股價，但他們卻應該考慮這個產業五年後的發展趨勢。

That actually is a -- question, Fred. So thinking about announcements and catalysts like what should we look for from MARA to know that like this strategy is taking form and we can start to frame an economic story or accretive story around some of these initiatives. Like what are the milestones and announcements we should be looking for from you guys?

弗雷德，這確實是個問題。因此，我們應該思考一些公告和催化劑，例如我們應該從 MARA 中關注什麼，才能知道這項策略正在形成，我們可以開始圍繞這些舉措構建一個經濟故事或增值故事。我們應該期待你們發布哪些里程碑事件和公告？

So here's what I think you should look for. Four years ago, I made a presentation at a conference where I said that Bitcoin miners are either going to be energy companies or be owned by energy companies. I think what you should look for is when large energy companies start signing partnership agreements with companies like us to monetize their energy assets at large scale.

所以我認為你應該注意以下幾點。四年前，我在一次會議上做了一個演講，我說比特幣礦工要嘛會成為能源公司，要嘛會被能源公司擁有。我認為你應該關注的是，大型能源公司何時開始與我們這樣的公司簽署合作協議，以大規模地將其能源資產貨幣化。

That will tell you that if that happens to be of that they have chosen us to do with because they feel we are the best option for them to maximize the value of the electrons that they produce. That's one step. The next step is as you start seeing customers using more and more inference AI. And you see us reporting a greater and greater mix of inference AI in our data centers.

那說明，如果真是那樣，他們選擇與我們合作是因為他們認為我們是他們最大化所產生電子價值的最佳選擇。這是第一步。下一步就是您開始看到客戶越來越多地使用推理人工智慧。您可以看到，我們的資料中心中推理人工智慧的應用比例越來越高。

And the real metric you should look for is what is our profit per megawatt hour that we talk about. It's not a GAAP measure. So it's not going to be reported that way, but you can think of it as an operational KPI where the profit we can generate from every megawatt hour of energy that we consume or produce, is a data point that our investors will be able to see and that will directly correlate to our profitability and ability to cash-generating business.

而你真正應該關注的指標是我們所說的每兆瓦時的利潤是多少。它不是GAAP指標。所以不會以這種方式報告，但你可以把它看作是一個營運KPI，我們從消耗或生產的每一兆瓦時能源中產生的利潤，是一個我們的投資者可以看到的數據點，它將直接與我們的盈利能力和現金創造能力相關。

Okay. Fair. And just to make sure and I apologize to so many questions. Are you looking to sign colocation clients or deals for this site in West Texas? Or is this something that you're thinking about putting your own machines in --

好的。公平的。還有一點要確認，另外，對於問了這麼多問題，我深感抱歉。您是否正在為位於德州西部的這個資料中心尋找託管客戶或洽談合作？或者，您是不是在考慮把自己的機器放進去？--

It gives us I'm not going to answer the question directly because I think our competitors spend more than enough time listening to what I say and then emulating it. So I'm just going to say it this way. It gives us maximum optionality to decide what we want to do with whom.

這讓我覺得我不會直接回答這個問題，因為我認為我們的競爭對手已經花了太多時間傾聽我的話，然後模仿我。所以我就這樣說吧。它賦予我們最大的選擇權，讓我們能夠決定與誰合作。

Got It. Okay. I want to bring it up because you didn't mention signing a colocation as like a milestone.

知道了。好的。我想提一下這件事，因為你沒有把簽署託管協議當作一個里程碑事件來提及。

No, you see, if I can operate inference AI and make money on it without signing a colocation facility. That will give you a little bit more insight into what the business model might actually be. Because think about the best thing about our Bitcoin mining business is we don't have a customer. What's the hardest thing all these colocation deals have? Does that have to go into a customer?

不，你看，如果我能在不簽署託管設施協議的情況下運行推理人工智慧並從中賺錢的話。這將讓你對商業模式的實際運作方式有更深入的了解。想想我們比特幣挖礦業務最大的好處就是我們沒有客戶。所有這些託管交易中最難的是什麼？這必須提交給客戶嗎？

Yes. Okay. Okay. People say change my opinion when the facts change, and that's a pretty -- it seems like a pretty major shift for MARA like I said, you guys bought GPUs, I guess, in the last three months and you start to run them, like what in your mind has changed that has changed your opinion or has your opinion changed and strategically, it seems like the company is kind of pivoting. Talk to me about that. Like what have you learned or gleaned in the last couple of months or quarters it is shift.

是的。好的。好的。人們常說，當事實改變時，我的觀點也會改變。這似乎對 MARA 來說是一個相當大的轉變，就像我之前說的，你們在過去三個月裡購買了 GPU，並且開始運行它們，那麼是什麼改變了你們的想法，從而改變了你們的觀點？或者說，你們的觀點是否改變了？從戰略上看，該公司似乎正在進行某種轉型。跟我說說這件事。就像你在過去幾個月或幾季中學到或獲得了什麼一樣，這是一種轉變。

Yes, Reggie, I wish I could tell you that I had a lightning bolt strike me and I came to Tiffany. But this is -- we're executing the strategy we decided to execute over a year ago. It's just we have decided not to go totally open to market and tell people what we're doing because it just gives our competitors insight into what we do and they can emulate it. and prefer to control the timing on how we talk about what we're doing.

是的，雷吉，我真希望我能告訴你，我被閃電擊中後就來到了蒂芙尼身邊。但這就是——我們正在執行一年多前決定執行的策略。我們只是決定不完全公開市場，不告訴人們我們在做什麼，因為這會讓競爭對手了解我們的業務，他們可以模仿我們。我們更傾向於控制我們談論業務的時機。

But I've been talking for the longest time about inference at the edge and that's where we would make our market in the marketplace. And we are -- we've talked a long time about owning power and the desire to run our business based on controlling energy assets that were fully virtually integrated. And we're doing that.

但我一直以來都在談論邊緣推理，而這正是我們在市場上的立足點。我們一直以來都在談論擁有權力，以及希望透過控製完全虛擬整合的能源資產來經營我們的業務。我們正在這樣做。

There's no change in strategy. There's no pivot. It's just we have been purposely operating more like a startup in the sense that we have really wanted to make sure that we had everything in place so that as the market becomes aware of what we're doing, they just start seeing kind of announcement after announcement after announcement that just gives them more and more confidence in that we're executing on the vision that we set out a year ago.

策略沒有改變。沒有轉折點。我們只是有意地以新創公司的方式運作，因為我們真的想確保一切就緒，這樣當市場了解我們正在做的事情時，他們就會看到一個又一個的公告，這讓他們越來越相信我們正在執行一年前製定的願景。

Yes. No, I'd say from where I sit and I think about all the pieces you guys have, there are a lot of pieces, and I'm not starting to figure out how to put it all together, but it seems like you guys have a lot of ways to kind of win here. I guess we just have to kind of sit back and wait for those announcements as they kind of come through. I know we've kind of spent a lot of time on this. I hope it wasn't a wasted time for people.

是的。不，就我目前所處的位置來看，考慮到你們擁有的所有資源，資源確實很多，我還沒開始弄清楚如何將它們全部整合起來，但看起來你們有很多種獲勝的方法。我想我們只能靜觀其變，等待官方公告發布了。我知道我們已經在這上面花了很多時間。我希望這對大家來說沒有浪費時間。

Maybe you could shift gears a little bit and talk about your like sovereign and foreign government initiatives and things that are going on there. Like one of the questions, I have you think about this, what do you think gives you guys a right to win in the sovereign have you kind of load management space versus competitors? Who's been competing with you?

或許你可以稍微轉換話題，談談你所在國家和外國政府的舉措以及那裡正在發生的事情。就像我問你的一個問題，你認為是什麼讓你們在主權負載管理領域相對於競爭對手贏得勝利？誰在跟你競爭？

I think -- so there are a couple of ways to look at it. Most of our competitors enter a marketplace by partnering with somebody or contracting for power. They don't bother talking to the government because they're afraid that if they do, they may not be allowed to do what they want to do. And that's the case in a lot of places in the Middle East.

我認為——所以可以從幾個角度來看待這個問題。我們的大多數競爭對手都是透過與他人合作或簽訂電力合約進入市場的。他們不願與政府溝通，因為他們害怕如果溝通的話，他們可能就無法做自己想做的事了。中東很多地方都是這種情況。

We, on the other hand, chose to do it the other way. So in UAE, where we've been operating now for a couple of years, we chose to directly go and work with the sovereign. So we partnered with ADQ and IHC and operate a joint venture together with them where we balance the grid in UAE. It's one of the most advanced liquid immersion technology sites in the Middle East. The only one that's bigger than that is the liquid merchant site we operate in Granbury.

而我們則選擇了另一種方式。所以，在阿聯酋，我們已經在那裡運作了幾年，我們選擇直接與該國政府合作。因此，我們與 ADQ 和 IHC 合作，共同經營一家合資企業，在阿聯酋平衡電網。它是中東地區最先進的液體浸沒技術基地之一。唯一比它更大的就是我們在格蘭伯里經營的行動商家網站。

And so that has given us the reputation of being somebody who works well with government entities follows the rules and is focused on being a good to grid citizen in balancing the grid. So when we talk to people in other countries such as in France, such as in the UK, such as in Kenya, in Saudi Arabia in other places. We are welcomed with open arms because we are focused on how can we make your grid more efficient and more effective? How can we make sure that every electron generators generate maximum value?

因此，我們贏得了與政府機構良好合作、遵守規則、致力於成為電網平衡良好公民的聲譽。所以當我們與其他國家的人交談時，例如在法國、英國、肯亞、沙烏地阿拉伯等地。我們受到熱烈歡迎，因為我們專注於如何提升你們電網的效率和效能？如何確保每個電子產生器都能產生最大價值？

And we are here to be a good grid citizen, and we are here to operate such that your grid becomes more stable, and it becomes easier for you to bring on new types of loads and see them AI data centers or whatever. And the challenge, the way most people see it, that takes time, right? I have been crossing the Atlantic very frequently. But I have been having meetings in at the top levels of government, and we have a lot of support. We certainly have seen lot of support on the European side because there are certain dynamics in Europe that create very large opportunities for us.

我們來到這裡是為了成為電網的良好公民，我們的營運旨在使您的電網更加穩定，使您更容易引入新型負載，例如人工智慧資料中心或其他任何負載。而大多數人認為，真正的挑戰在於需要時間，對吧？我經常往返於大西洋兩岸。但我一直在與政府高層會面，我們得到了許多支持。我們確實在歐洲方面獲得了極大的支持，因為歐洲的一些發展趨勢為我們創造了巨大的機會。

And so same thing exists in Saudi Arabia, for example, in other places. And we think that we -- it's worth our effort to spend the time and takes the time to do this carefully and prudently and well thought out so that we're able to execute successfully and have long-term success in the countries.

例如，沙烏地阿拉伯和其他地方也存在同樣的情況。我們認為，花時間認真、謹慎、周全地做好這件事是值得的，這樣我們才能成功執行，並在這些國家取得長期的成功。

Because if we're friends with the government, then we have the advantage that as they look to expand what they're doing, if we are a good partner, they will come to us and say, hey, we want to do more with you. And that's the type of relationship we want to have with our partners across industry, be it governments, vendors or end customers.

因為如果我們和政府是朋友，那麼我們就擁有了優勢，當他們尋求擴大其業務範圍時，如果我們是一個好的合作夥伴，他們就會來找我們說，嘿，我們想和你們做更多的事情。而這正是我們希望與各行各業的合作夥伴（無論是政府、供應商或最終客戶）建立的關係。

And you haven't talked about Bitcoin mining at all, no running show. Just an update there. Love to hear about the stuff that's happening in the wind farm and some of your flared gas initiatives. Maybe talk a bit about Auradine. And then, I guess, your plans for growing hash rate here and how you think about that in the context of kind of where cash price is and why it makes us to continue to grow your hash rate at these levels.

你根本沒談到比特幣挖礦，沒有相關討論。更新一下情況。很想了解風力發電場的最新情況以及你們的一些天然氣燃燒處理項目。或許可以稍微聊聊奧拉丁。然後，我想，你們計劃如何提高這裡的算力，以及你們如何看待當前的現金價格，以及為什麼這促使我們繼續在目前的水平上提高算力。

Yes. So maybe I'll look at this in kind of a somewhat reverse order. So there is more hash rate coming online every day from lots of players. There are very well capitalized to the companies who are not public who are -- have access to huge amounts of capital who have a stated goal of becoming the largest bitcoin miner in the world. And if we don't grow our cash rate, we will have an ever-decreasing amount of the global hash rate and produce ever decreasing amounts of Bitcoin.

是的。所以，或許我會以一種略微相反的順序來看這個問題。因此，每天都有大量玩家在線上提供更多的哈希率。那些資金雄厚的非上市公司——它們擁有巨額資金，並公開宣稱要成為世界上最大的比特幣礦商。如果我們不提高現金利率，全球哈希率就會不斷下降，比特幣的產量也會不斷下降。

And we think that it's our duty to continue to grow hash rate, not just in the United States but globally to support the security and diversity of the Bitcoin blockchain and the Bitcoin network because we don't want it to be dominated by any small handful of players. And so we believe it's our duty to continue to grow cash rate.

我們認為，我們有責任繼續提高哈希率，不僅在美國，而且在全球範圍內，以支持比特幣區塊鏈和比特幣網路的安全性和多樣性，因為我們不希望它被少數幾個參與者所壟斷。因此，我們認為繼續提高現金利率是我們的責任。

So how do we do that economically, we do it with low-cost power, which we can control. which ties to the MPLX deal, it ties to what we're doing with our wind farm Texas. It ties to what we're doing with flare gas. We have doubled by the end of this year, we'll have doubled our flare gas capacity, and we're going to continue to grow that. The wind farm is fully built out from a data center perspective, and that's running.

那我們要如何在經濟上實現這一點呢？我們使用低成本的電力，而且我們可以控制電力供應。這與 MPLX 的交易有關，也與我們在德州的風力發電場計畫有關。這和我們對火炬氣的處理方式有關。到今年年底，我們的火炬氣處理能力將翻一番，而且我們將繼續擴大這一規模。從資料中心的角度來看，風力發電場已經完全建成，並且正在運作。

And we're going to continue to look at opportunities to require more energy at low cost that we can then allocate between Bitcoin mining or AI. You have to kind of think of us as we are going to own lots of our electronics, and we're going to put those electrons to best possibly use.

我們將繼續尋找以低成本獲取更多能源的機會，然後將這些能源分配給比特幣挖礦或人工智慧。你應該這樣想：我們將擁有大量的電子產品，我們將盡可能充分利用這些電子產品。

In regards to Auradine, Auradine's more recent hydro model, which competes very well with the Bitcoin and other vendors models is doing well. We're deploying -- in our fleet. We're not putting exclusively Auradine at this point. There are still different machines, different characteristics that are really good for different environments, and we have a lot of different environments. And so we're continuing to deploy a mix of systems.

就 Auradine 而言，Auradine 最新的水力發電模型表現良好，與比特幣和其他供應商的模型相比，該車型具有很強的競爭力。我們正在部署——在我們的艦隊中。目前我們還沒有完全專注於 Auradin。仍然存在不同的機器，不同的特性，它們非常適合不同的環境，而我們有很多不同的環境。因此，我們將繼續部署多種系統。

But over time, it would be logical to feel that we're going to add more and more Auradine to our fleet. Their systems offer them very unique capabilities, especially around load balancing that in a model such as the one that is beginning to gain steam in Texas, where the utility wants to regulate your curtailment and shut you off and turn you on.

但隨著時間的推移，我們很可能會認為，我們的艦隊將會不斷增加奧拉丁級戰艦。他們的系統為他們提供了非常獨特的功能，尤其是在負載平衡方面，例如在德克薩斯州開始流行的那種模式，公用事業公司想要調節你的用電量，切斷你的電源，然後再給你供電。

That requires special capabilities in the miners, and that's something that exists in the Auradine systems. And so as more and more utilities start looking for those capabilities amongst miners who are on grid, I think they will continue to gain some market share there.

這需要礦工具備特殊能力，而奧拉丁系統恰好具備這種能力。因此，隨著越來越多的公用事業公司開始在併網礦工中尋找這些能力，我認為他們將繼續獲得一些市場份額。

Other than that, they have spun out some very interesting AI-related businesses, one or escape, which is around securing large language models, which recently had a lot of positive reviews at the RSA show earlier this year and then also scaleup, which is a start-up around ultra-high-speed cluster interconnect switch technology. So that has been a great investment for us, and we continue to look for investments like that where we can acquire or build technologies that can become part of our solutions over time.

除此之外，他們還衍生出了一些非常有趣的人工智慧相關業務，例如專注於大型語言模型安全的 Escape，該公司在今年早些時候的 RSA 大會上獲得了許多好評；以及專注於超高速集群互連交換機技術的初創公司 Scalup。所以這對我們來說是一項很棒的投資，我們將繼續尋找類似的投資機會，收購或開發能夠隨著時間的推移成為我們解決方案一部分的技術。

And I guess last one for me. You kind of talked about it earlier, but obviously, a lot of market cap, a lot of value created in the Bitcoin mining space amongst the publicly traded guys. I'd argue that you guys haven't received or gotten your share of that. Like what do you think the market is missing. And hopefully, we'll come to appreciate in the near term or medium term.

我想這應該是我最後一個問題了。你之前也提到過，很明顯，比特幣挖礦領域在上市公司中創造了巨大的市值和價值。我認為你們還沒有得到或享受你們應得的那一份。你認為市場目前缺乏什麼？希望在不久的將來或中期內，我們能夠意識到這一點。

Yes. I mean I think the key for us is the floor on the valuation of our stock is essentially the value of our Bitcoin Holdings. And people don't put a lot of value on the Bitcoin mining infrastructure or the Bitcoin mining business per se. And I think as our business continues to evolve, especially with the energy generation story and as AI becomes a bigger piece of this and we generate more profit per megawatt hour consumed we'll start getting more attention from people. And I think you'll start seeing people realizing really the benefit of what we're doing in our model, and we'll get more credit for that.

是的。我的意思是，我認為對我們來說，關鍵在於我們股票估值的底線本質上就是我們比特幣持有量的價值。人們並沒有給予比特幣挖礦基礎設施或比特幣挖礦業務本身很高的價值。我認為，隨著我們業務的不斷發展，尤其是在能源生產領域，隨著人工智慧在其中扮演越來越重要的角色，以及我們每消耗一兆瓦時電力所創造的利潤不斷增加，我們將開始受到人們更多的關注。我認為你會開始看到人們真正意識到我們模式的好處，我們也會因此獲得更多認可。

Reggie, just to add to that, the power capacity that we have secured through these transactions that puts us at the forefront. And here's where the actual value flows with Bitcoin mining option value between AI-ready assets, our operational flexibility with integrated power. That's what's going to drive value for our stockholders from a long-term perspective.

雷吉，我還要補充一點，我們透過這些交易獲得的電力容量使我們處於領先地位。而真正的價值就在於此，也就是人工智慧就緒資產之間的比特幣挖礦選擇權價值，以及我們透過整合電力實現的營運彈性。從長遠來看，這將為我們的股東創造價值。

Thank you, guys. Congrats in the quarter.

謝謝大家。恭喜你本季取得佳績。

Thank you.

謝謝。

Thanks, Reggie. We appreciate it. Most of the questions that we received from our retail shareholders have been answered. We're obviously running -- short on time, but thanks, everyone, for joining us today. If you have any questions that were not answered during today's call, please feel free to contact our Investor Relations team at ir@mara.com. Thanks very much, and enjoy the rest of the day.

謝謝你，雷吉。我們非常感謝。我們已經解答了零售股東提出的大部分問題。我們時間很緊，但還是要感謝大家今天加入我們。如果您有任何在今天的電話會議中未得到解答的問題，請隨時聯繫我們的投資者關係團隊，郵箱地址是ir@mara.com。非常感謝，祝您今天餘下的時間愉快。