Акции Canaan выросли на 18% после рекордного заказа на 50 000 майнеров Avalon в США

cryptonews.ruPublicado em 2025-10-15Última atualização em 2025-10-15

Акции Canaan (NASDAQ: CAN) подскочили на 18% после открытия американских рынков в четверг. Рост произошел после того, как производитель оборудования для майнинга биткоинов объявил о крупнейшем заказе на покупку за три года.

Производитель оборудования для майнинга биткоинов сообщил, что некая американская майнинговая организация, название которой не разглашается, согласилась приобрести более 50 000 единиц новейших устройств Avalon A15 Pro. Поставка оборудования запланирована на четвертый квартал.

Каждый A15 Pro обеспечивает хешрейт 218 терахеш в секунду. Это означает, что общий заказ представляет собой более 10 EH/s вычислительной мощности после развертывания.

Canaan утверждает, что масштаб сделки подчеркивает возобновившийся интерес институциональных инвесторов к эффективной майнинговой инфраструктуре в США. Это происходит несмотря на то, что сложность сети и колебания цен на хешрейт негативно сказываются на прибыльности майнинга.

Это объявление дополняет серию развертываний устройств Avalon компаниями Cipher Mining и CleanSpark в этом году. Также компания Canaan расширяет собственные майнинговые мощности за счет нераспроданных майнеров Avalon.

Хотя имя покупателя не разглашается, суммарное обязательство в размере более 10 EH/s делает эту сделку одним из крупнейших единовременных заказов на оборудование на рынке США за последний год.

Leituras Relacionadas

In Just 11 Days, Claude Rewrote Millions of Lines of Code, an Epic AI Engineering Feat Sparks Fury

In just 11 days, Bun's founder Jarred Sumner used Anthropic's Claude AI models to rewrite its million lines of code from Zig to Rust. This move sparked significant controversy, particularly from Zig's creator, Andrew Kelley, who publicly criticized Sumner's engineering practices and the decision to use AI for such a massive rewrite. Bun, a high-performance JavaScript/TypeScript runtime and rival to Node.js, was originally written in Zig. After Anthropic acquired Bun, the team encountered persistent stability and memory safety bugs in the Zig codebase. These issues, combined with Zig's strict policy against LLM-generated code, led to the decision to rewrite in Rust. The rewrite was executed using Claude AI tools at an estimated API cost of $165,000, dramatically reducing the expected time and financial cost. Andrew Kelley's response was scathing. He blamed the original bugs on poor engineering habits, calling Bun's Zig code a collection of "hacks on top of hacks." He expressed relief that Bun was no longer associated with Zig, fearing it would misrepresent the language and attract low-quality, AI-generated contributions. The tech community is divided; some view Kelley's critique as unprofessional, while others see it as a defense of engineering integrity. A major concern about the AI-driven rewrite is the resulting code quality. The translation from Zig left approximately 27,000 lines of unsafe Rust code, raising fears about long-term maintainability and technical debt. The debate centers on whether this project is a milestone in AI-assisted development or a future maintenance nightmare.

marsbitHá 29m

In Just 11 Days, Claude Rewrote Millions of Lines of Code, an Epic AI Engineering Feat Sparks Fury

marsbitHá 29m

From Auto Finance to Bitcoin to AI Engines: An Analysis of Cango's 'What Not to Do' Strategy

From Auto Finance to Bitcoin and Now AI: Cango's "What Not to Do" Strategy Cango, a Chinese auto finance platform that went public on the NYSE in 2018, is undergoing its third major transformation. After selling its entire auto business in 2024, it pivoted to become a large-scale Bitcoin miner, acquiring 50 exahash of mining rigs from Bitmain. However, its true goal was never Bitcoin, but owning and controlling energy infrastructure. Now, Cango is pivoting again. While most listed Bitcoin miners are leasing power to giant hyperscalers for AI training clusters, Cango is taking the opposite path. It has launched an AI inference subsidiary called EcoHash, focusing not on training but on distributed inference. The company's strategy hinges on the insight that over 70% of mining industry power is controlled by small, independent sites (10-50 MW), which are too small for hyperscalers but ideal for low-latency AI inference. Cango aims to partner with these small operators, providing the AI technology, customers, and financing through its EcoLink software layer, which can distribute workloads across sites for reliability. Cango maintains a hybrid model, running roughly 31.7 EH/s of Bitcoin mining for cash flow while aggressively cleaning its balance sheet—slashing long-term debt by 94.5% to $30.6 million and raising $75 million for its AI venture. Its first AI deployment will be at a 50 MW site in Georgia. The strategy faces skepticism, given the high costs of converting mining sites and the potential for an AI bubble. However, Cango's leadership believes discipline around "what not to do"—avoiding direct competition with hyperscalers in training—positions it to capture the long-tail demand for distributed AI inference power.

Foresight NewsHá 45m

From Auto Finance to Bitcoin to AI Engines: An Analysis of Cango's 'What Not to Do' Strategy

Foresight NewsHá 45m

Strategy's Bitcoin Sales Cap Far Exceeds $1.25 Billion: A Detail the Market Overlooked

The article discusses how MicroStrategy's potential Bitcoin sales go far beyond the announced $1.25 billion "reserve-building capacity." It clarifies a key distinction in the company's "BTC Monetization Program": selling Bitcoin to *build* a new dollar reserve (the $1.25B cap) versus selling to *replenish* the existing USD Reserve after it's used for expenses like preferred share dividends. The recent $216M BTC sale for dividend payments was a "replenishment," leaving the headline $1.25B building quota untouched. The plan actually outlines three potential funding pools from BTC sales: 1) Building the reserve ($1.25B cap), 2) Covering preferred share/ debt costs (no specified cap), and 3) Funding buyback programs (up to $20B). This means the structured sales potential exceeds $30 billion, not including uncapped replenishment sales. The piece argues this marks MicroStrategy's shift from a passive "buy-and-hold" Bitcoin proxy to an actively managed entity using BTC as a balance-sheet tool to manage its complex capital structure (common stock, preferred shares, debt, reserve). This creates new dynamics and potential conflicts, as actions benefiting one part (e.g., selling BTC to pay dividends) may pressure another (e.g., undermining the "never sell" narrative). Investors must now parse the company's specific terminology ("build" vs. "replenish") to understand the true scope of future BTC sales, which is significantly larger than the market initially perceived.

marsbitHá 52m

Strategy's Bitcoin Sales Cap Far Exceeds $1.25 Billion: A Detail the Market Overlooked

marsbitHá 52m

Goldman Sachs Report Deconstructs the Competitive Landscape of China's AI Large Models: Who Will Be the Long-Term Winner?

Goldman Sachs analyzes China's AI large language model (LLM) landscape, identifying key players and a strategic shift towards efficiency and global expansion. The report highlights that Chinese open-source/open-weight models are closing the performance gap with top global proprietary models at significantly lower cost, driven by architectural innovations like MoE. This enables a "two-tier" market: a high-end segment (e.g., GLM5.2, Qwen3.7 Max) with pricing at ~$1 per million tokens, and a low-end, price-sensitive global segment. Open-source strategies aid adoption but limit monetization, as deployments via third-party platforms (e.g., AWS Bedrock, Alibaba Cloud) may not generate direct revenue for model creators. The industry is thus moving towards "open-weight + community license" models with revenue-sharing to improve unit economics. Internationally, the focus is shifting from "token maximization" to ROI-driven enterprise adoption, particularly in non-U.S. markets. Major cloud platforms are integrating Chinese models (e.g., DeepSeek, MiniMax). Using a competitive framework based on pricing power, cost advantage, and financial strength, Goldman Sachs identifies **Zhipu AI** and **DeepSeek** as leaders in foundational text models, and **ByteDance** (with Seedance) leading in multimodal/video generation. **MiniMax** and **Kuaishou** are also rated favorably. The firm forecasts China's AI model API/subscription revenue growing from ~RMB 35bn (2026E) to RMB 879bn by 2030.

marsbitHá 52m

Goldman Sachs Report Deconstructs the Competitive Landscape of China's AI Large Models: Who Will Be the Long-Term Winner?

marsbitHá 52m

Trading

Spot
活动图片