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 维持对 Aster Labs 的买入评级，将目标价从 $260 上调至 $425

分析师认为产品增长广泛，XPU 含量上升，Scorpio X 产能爬坡以及 Leo CXL 动能增强。

Astera Labs 关于 NPO/CPO：

“一旦 NPO 部署完成且数据库持续增长，我们将开始看到 CPO 的部署。我们认为 2027 年是 NPO 部署的年份，而 2028 年及以后则是 CPO 部署的时间。”

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摩根士丹利：光通信 vs 铜缆

你认为 2027、2028、2029 年等年份的光通信规模扩张机会如何？这与英伟达生态系统及路线图有何关联？

A：我们认为明年将出现小规模的外包采用，外包部分的渗透率约为 10-15%。我们确实认为在 2029 年 Feynman 架构推出之前，共封装光学（CPO）的采用率较低。2028 年 CPO 的采用率仅为个位数，真正的大规模应用将在 2029 年。

你们将总可寻址市场（TAM）上调至 730 亿美元，是去年水平的 4 倍，请谈谈推动这一增长的因素，以及这与市场共识和买方预期相比如何？

A：主要驱动力之一是资本支出数据点是我们去年预期的两倍，这是增长的一个方面。另一方面，讨论中的集群规模是规模最大的规模扩展网络。我们从 8 节点发展到 72 节点，然后在接下来的几代中从几百个发展到上千个。这起到了规模扩展乘数的作用。

谈谈 Lumentum、Coherent 和 Corning 之间的风险敞口。谁的风险敞口更大或更小，是否存在细微差别？

A：对于外包场景下的 CPO，这对 Lumentum 总体上是积极的。对 Corning 的影响不一定很大。对于 Coherent，他们需要平衡其现有的收发器业务。对 Lumentum 最为有利，因为他们在收发器侧唯一的客户是 Google，而 Google 不会采用 CPO。对于规模扩展内的 CPO，这三家公司都有机会。这是铜被光纤取代并由 Coherent 和 Lumentum 制造的光引擎和激光器照亮的领域。就整体风险敞口而言，由于 AI/数据中心收入占比更大，Lumentum 拥有更大的催化剂。这对 Coherent 和 Lumentum 都是增量收益。Lumentum 排第一，Coherent 或 Corning 排第二。

告诉我关于让股价兴奋的 Corning Glass Bridge 公告是怎么回事？

A：这并不是新公告。这是他们 2025 年发布的一篇论文，以及一次重新聚焦市场对这项技术关注的演示。它已经是该公司几个月前提到的 100 亿美元光子学目标的一部分。

就光通信领域的催化剂而言，10 月举行的 OCP（开放计算项目）会议备受关注。你期待从中听到什么？

A：我们认为这将是一个催化剂，因为它提供了更多超大规模运营商行为的信息。OCP 将让我们有机会看到超大规模运营商的路线图，重点关注 CPO、NPO 的采用以及相关供应商。

铜缆仍然是 2026 年和 2027 年的主题。我们已经看到对 ASICs 的持续热情。铜缆在这种动态下处于怎样的有利位置？谁是受益者？

A：通过使用重定时器（retimers）和更好的 SerDes，可以延长铜缆的使用寿命。在切换到全光之前，铜缆还有很长的路要走。在进入 100% 光之前，我们可能会看到一个混合环境。规模扩展中的一个重大辩论是，随着新的 XPU 和 Nvidia GPU 替代方案的 ramping，除了 NVLink 之外，哪种 fabric 和协议将成为主导。这里的主要辩论是在 UALink 和以太网之间。以太网依赖于 Broadcom 的新 ASIC 在 2027 年下半年到 2028 年的 ramping，我们认为 Broadcom 将有機會将 XPU 解决方案与网络产品捆绑销售，并在以太网方面处于非常有利的地位。至于 UALink，这对 Marvell 和 Astera Labs 具有高选择性。Astera 拥有 Trainium 3 的规模扩展交换机，这是一种基于 PCIe 的解决方案。我们认为客户最终会转向 UA Link。

你将 Keysight 视为研发方面的中立赢家，无论铜缆还是光通信的时间表如何。解释你的论点，为什么你认为它会领先？

A：Keysight 在多个方面受益于 AI。首先，它受益于正在讨论的不同类型的架构，所有这些架构都需要在实验室中使用他们的设备进行测试。其次，当你向更高速率移动时（例如 400g 激光 vs 200g），需要更复杂的测试。第三，当架构频繁变化时，比如每两年一次，这会促进他们的业务。测试的架构多样性很重要。

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