Astera Labs

📢 𝗝𝗨𝗦𝗧 𝗜𝗡: $Astera Labs(ALAB.US) Astera Labs Launches New Leo Memory Solutions for Agentic AI Infrastructure

👉 𝗞𝗲𝘆 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀:

➤ 𝗔𝘀𝘁𝗲𝗿𝗮 𝗟𝗮𝗯𝘀 launches new 𝗟𝗲𝗼 𝗫-𝗦𝗲𝗿𝗶𝗲𝘀 and 𝗟𝗲𝗼 𝟮 memory controllers.

➤ Leo X-Series targets 𝗞𝗩-𝗰𝗮𝗰𝗵𝗲-intensive, long-context agentic AI inference workloads.

➤ Leo X-Series delivers up to 𝟲𝟮% faster time-to-first-token.

➤ Platform delivers up to 𝟮𝟮% more tokens per second.

➤ Leo 2 doubles 𝗺𝗲𝗺𝗼𝗿𝘆 𝗯𝗮𝗻𝗱𝘄𝗶𝗱𝘁𝗵 and capacity versus previous generation.

➤ New controllers support 𝗗𝗗𝗥𝟰, 𝗗𝗗𝗥𝟱, 𝗣𝗖𝗜𝗲 𝟲 and 𝗖𝗫𝗟 𝟯.𝟮.

➤ Leo 2 enables memory expansion, pooling, sharing, and 𝗗𝗗𝗥𝟰 reuse.

➤ Astera reports growing design wins across 𝗔𝗜 𝗹𝗮𝗯𝘀, hyperscalers, and neoclouds.

➤ New Leo products are 𝘀𝗮𝗺𝗽𝗹𝗶𝗻𝗴 𝘁𝗼𝗱𝗮𝘆 with hyperscaler customers.

➤ Development involved 𝗔𝗠𝗗, 𝗔𝗿𝗺, 𝗜𝗻𝘁𝗲𝗹 and major memory suppliers.

👉 𝗪𝗵𝘆 𝗧𝗵𝗶𝘀 𝗠𝗮𝘁𝘁𝗲𝗿𝘀:

➤ Agentic AI is rapidly increasing demand for 𝗺𝗲𝗺𝗼𝗿𝘆 𝗰𝗮𝗽𝗮𝗰𝗶𝘁𝘆 and bandwidth.

➤ Faster KV-cache access can improve 𝗔𝗜 𝗶𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 economics and responsiveness.

➤ Memory pooling and reuse could reduce expensive 𝗗𝗥𝗔𝗠 over-provisioning.

➤ Growing design wins could expand Astera's exposure to 𝗿𝗮𝗰𝗸-𝘀𝗰𝗮𝗹𝗲 𝗔𝗜 infrastructure.

👉 𝗘𝘅𝗽𝗲𝗿𝘁 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁𝘀:

𝗠𝗮𝘁𝘁 𝗞𝗶𝗺𝗯𝗮𝗹𝗹, Vice President and Principal Analyst at Moor Insights & Strategy:

“Agentic AI adoption is outpacing the industry's ability to provision memory for it, and that gap is widening every quarter," said Matt Kimball, vice president and principal analyst at Moor Insights & Strategy. "That growth is landing at the worst possible time for memory supply, with DDR5 tight and pricing climbing, so every gigabyte already deployed has to work harder. The new Leo X-Series and Leo 2 E and P-Series Smart Memory Controllers immediately address KV-cache-intensive AI workloads, improve memory utilization, and reliably reuse previously deployed memory across both AI and general-purpose cloud infrastructure, instead of simply buying more of it."

𝗧𝗵𝗮𝗱 𝗢𝗺𝘂𝗿𝗮, Senior Vice President, Compute Connectivity Group at Astera Labs:

“Agentic AI is where the economics of AI infrastructure are being decided, and those economics depend on putting every usable gigabyte of memory to work,” said Thad Omura, senior vice president, Compute Connectivity Group at Astera Labs. “The enhanced Leo family gives infrastructure providers purpose-built ways to connect memory to accelerators, CPUs, and hosts across the rack—turning previously deployed and stranded capacity into a resource that new AI and cloud workloads can use. We're seeing that translate into broader customer engagement across AI labs, hyperscalers, and neoclouds.”

𝗥𝗼𝗯𝗲𝗿𝘁 𝗛𝗼𝗿𝗺𝘂𝘁𝗵, Corporate Vice President, Architecture and Strategy at AMD:

“Agentic AI is increasing demand for balanced systems that can move and process more data without sacrificing efficiency. AMD EPYC processors deliver leadership performance, exceptional memory bandwidth and capacity, and high-speed I/O across the broadly deployed x86 platform. Our collaboration with Astera Labs around CXL extends that foundation, giving customers greater flexibility to scale memory-intensive AI and cloud workloads and improve infrastructure utilization.”

𝗘𝗱𝗱𝗶𝗲 𝗥𝗮𝗺𝗶𝗿𝗲𝘇, Vice President of Go-To-Market, Cloud AI, Arm:

“As AI infrastructure evolves, agentic AI, reinforcement learning and database workloads are driving demand for higher-capacity memory. Arm and Astera Labs are working together to pair Arm AGI CPU with Leo CXL Smart Memory Controllers, helping customers meet these growing requirements while maintaining scalable performance.”

𝗦𝗿𝗶𝗻𝗶 𝗞𝗿𝗶𝘀𝗵𝗻𝗮, Fellow at Intel Data Center Group:

"CXL was created to bring greater flexibility and efficiency to memory across the data center. Technologies like Astera Labs' Leo Smart Memory Controllers help turn that vision into reality, demonstrating how ecosystem innovation can help customers get more out of their AI infrastructure and support the next generation of data-intensive workloads."

𝗝𝗮𝗻𝗴𝘀𝗲𝗼𝗸 𝗖𝗵𝗼𝗶, Vice President of Product Planning Team at Samsung Electronics:

"We are contributing to the evolution of AI infrastructure through the development of CXL memory solutions designed to help address the growing memory demands of modern data centers. We are excited to collaborate with Astera Labs to help ensure our DRAM solution offer strong interoperability within the evolving CXL ecosystem, and remain committed to supporting a scalable, high-performance memory architecture for the AI era."

$Astera Labs(ALAB.US) | Needham 維持對 Aster Labs 的買入評級，將目標價從 $260 上調至 $425

分析師認為產品增長廣泛，XPU 含量上升，Scorpio X 產能爬坡以及 Leo CXL 動能增強。

Astera Labs 關於 NPO/CPO：

“一旦 NPO 部署完成且數據庫持續增長，我們將開始看到 CPO 的部署。我們認為 2027 年是 NPO 部署的年份，而 2028 年及以後則是 CPO 部署的時間。”

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摩根士丹利：光通信 vs 銅纜

你認為 2027、2028、2029 年等年份的光通信規模擴張機會如何？這與英偉達生態系統及路線圖有何關聯？

A：我們認為明年將出現小規模的外包採用，外包部分的滲透率約為 10-15%。我們確實認為在 2029 年 Feynman 架構推出之前，共封裝光學（CPO）的採用率較低。2028 年 CPO 的採用率僅為個位數，真正的大規模應用將在 2029 年。

你們將總可尋址市場（TAM）上調至 730 億美元，是去年水平的 4 倍，請談談推動這一增長的因素，以及這與市場共識和買方預期相比如何？

A：主要驅動力之一是資本支出數據點是我們去年預期的兩倍，這是增長的一個方面。另一方面，討論中的集羣規模是規模最大的規模擴展網絡。我們從 8 節點發展到 72 節點，然後在接下來的幾代中從幾百個發展到上千個。這起到了規模擴展乘數的作用。

談談 Lumentum、Coherent 和 Corning 之間的風險敞口。誰的風險敞口更大或更小，是否存在細微差別？

A：對於外包場景下的 CPO，這對 Lumentum 總體上是積極的。對 Corning 的影響不一定很大。對於 Coherent，他們需要平衡其現有的收發器業務。對 Lumentum 最為有利，因為他們在收發器側唯一的客户是 Google，而 Google 不會採用 CPO。對於規模擴展內的 CPO，這三家公司都有機會。這是銅被光纖取代並由 Coherent 和 Lumentum 製造的光引擎和激光器照亮的領域。就整體風險敞口而言，由於 AI/數據中心收入佔比更大，Lumentum 擁有更大的催化劑。這對 Coherent 和 Lumentum 都是增量收益。Lumentum 排第一，Coherent 或 Corning 排第二。

告訴我關於讓股價興奮的 Corning Glass Bridge 公告是怎麼回事？

A：這並不是新公告。這是他們 2025 年發佈的一篇論文，以及一次重新聚焦市場對這項技術關注的演示。它已經是該公司幾個月前提到的 100 億美元光子學目標的一部分。

就光通信領域的催化劑而言，10 月舉行的 OCP（開放計算項目）會議備受關注。你期待從中聽到什麼？

A：我們認為這將是一個催化劑，因為它提供了更多超大規模運營商行為的信息。OCP 將讓我們有機會看到超大規模運營商的路線圖，重點關注 CPO、NPO 的採用以及相關供應商。

銅纜仍然是 2026 年和 2027 年的主題。我們已經看到對 ASICs 的持續熱情。銅纜在這種動態下處於怎樣的有利位置？誰是受益者？

A：通過使用重定時器（retimers）和更好的 SerDes，可以延長銅纜的使用壽命。在切換到全光之前，銅纜還有很長的路要走。在進入 100% 光之前，我們可能會看到一個混合環境。規模擴展中的一個重大辯論是，隨着新的 XPU 和 Nvidia GPU 替代方案的 ramping，除了 NVLink 之外，哪種 fabric 和協議將成為主導。這裏的主要辯論是在 UALink 和以太網之間。以太網依賴於 Broadcom 的新 ASIC 在 2027 年下半年到 2028 年的 ramping，我們認為 Broadcom 將有機會將 XPU 解決方案與網絡產品捆綁銷售，並在以太網方面處於非常有利的地位。至於 UALink，這對 Marvell 和 Astera Labs 具有高選擇性。Astera 擁有 Trainium 3 的規模擴展交換機，這是一種基於 PCIe 的解決方案。我們認為客户最終會轉向 UA Link。

你將 Keysight 視為研發方面的中立贏家，無論銅纜還是光通信的時間表如何。解釋你的論點，為什麼你認為它會領先？

A：Keysight 在多個方面受益於 AI。首先，它受益於正在討論的不同類型的架構，所有這些架構都需要在實驗室中使用他們的設備進行測試。其次，當你向更高速率移動時（例如 400g 激光 vs 200g），需要更復雜的測試。第三，當架構頻繁變化時，比如每兩年一次，這會促進他們的業務。測試的架構多樣性很重要。

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