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📢 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 𝗺𝗮𝗶𝗻𝘁𝗮𝗶𝗻𝘀 𝗕𝘂𝘆 on 𝗔𝘀𝘁𝗲𝗿𝗮 𝗟𝗮𝗯𝘀, raises PT to $𝟰𝟮𝟱 from $𝟮𝟲𝟬

Analyst sees broad product growth, rising XPU content, a Scorpio X ramp and growing Leo CXL momentum.

Astera Labs on NPO/CPO:

"Once NPO gets deployed and database continues to increase, we will start to see CPO getting deployed. We look at it as 2027 being the year where NPO gets deployed, and then 2028 and beyond is when CPO gets deployed."

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Morgan Stanley: Optical vs Copper

How do you think about the optical scale up opportunity in 2027, 2028, 2029, etc, and how does that relates to the Nvidia ecosystem and roadmap?

A: We believe a small scale out adoption next year, with small volumes accounting for 10-15% penetration with scale out. We do think there are some low adoption with CPO until Feynman in 2029. Small, single digit adoption of CPO in 2028 and really scaling in 2029.

You took your TAM to $73B, 4x from a year ago, talk about the drivers of that and how that compares to consensus and buy side out there?

A: Driven by CapEx data points being 2x we were expecting last year, that is one vector of growth. The other is the cluster sizes being discussed are the biggest rivers of scale up network . We have gone from 8 to 72, then from a couple 100s to 1000s in the next couple generations. This acts as a multiplier to scale up multiplier.

Talk about the exposure among Lumentum, Coherent, and Corning. Are there nuances between who is more exposed, less exposed?

A: For CPO within scale out, it is generally positive for Lumentum. Doesn't necessarily changed a whole lot for Corning. With Coherent, they have to balance it out with transceiver business they have. For Lumentum it is the most positive because of the one customer they have on the transceiver side being google and they are not going to be adopting CPO. For CPO within scale up, it is opportunity for all 3. This is where copper gets replaced with fiber and lit up by lasers and optical engines made by Coherent an Lumentum. In terms of overall exposure, Lumentum has a bigger catalyst because of larger AI/DC revenue. It would be incremental for both Coherent and lumentum. Lumentum #1, Coherent or Corning #2.

Tell me about the Corning Glass Bridge announcement that got the stock excited?

A: This is not a new announcement. It was a paper they released in 2025 and a presentation they did that refocused the market on this technology. It is already part of the $10B photonics target the company discussed couple of months ago.

In terms of catalyst for optical space, OCP (Open Compute Project) coming in October has gone popular. What are you expecting to hear from this?

A: We think this will be a catalyst because it provides more exposure into hyperscaler behavior. OCP will give us a chance to see hyperscalers roadmap, it will focus on CPO, NPO adoption and the vendors involved.

Copper is still the story for 2026 and 2027. We have seen this continued enthusiasm for ASICs. How is copper well positioned for this dynamic? Who are the well positioned beneficiaries?

A: Copper life can be extended with use of retimers and better SerDes. Copper has a lot of runway before switching to optics. We will likely see a hybrid environment before going to 100% optics. A large debate in scale up is what fabric and protocol will become dominant other than NVLINK as we get into new XPUs and alternatives to Nvidia GPUs ramping. A big debate here is between UALink and ethernet. Ethernet is dependent on Broadcom's new ASICs ramping in 2H2027 into 2028, we think Broadcom will have opportunity to bundle XPU solutions with networking portfolio and are very well positioned in ethernet. On UALink, this is high optionality for Marvell and Astera Labs. Astera has the scale up switch for Trainium 3, this is a PCIe based solution. We think customers will want to move to UA Link eventually.

You consider Keysight as an agnostic winner in R&D, regardless of the copper vs optical timeline. Explain your thesis and why do you see it pulling ahead?

A: Keysight really ways in multiple ways when it comes to AI. First, it benefits from different types of architectures being discussed which all need to be tested with their equipment in labs. Second, when you move to higher speeds (400g laser vs 200g), it requires more complicated testing. Third, when architectures change frequently, like every 2 years, that boosts their business. The variety of architectures being tested matters.

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Morgan Stanley: Scale-Up Market

Massive Expansion of the Scale-Up Market

> 4x Market Surge: The AI scale-up network market is projected to reach a $70 billion+ opportunity by 2030, which is over four times the size estimated just a year ago ($17 billion by 2029).

> The Scale-Up Moat: Scale-up networks are essential because they allow thousands of GPUs/accelerators to operate seamlessly as a single supercomputer system, eliminating communication bottlenecks during modern frontier AI model training.

> Bigger Clusters: Cluster sizes are expanding rapidly. For example, NVIDIA’s roadmap has progressed from 72 GPUs in a single rack (Blackwell) to 144 GPUs (Vera Rubin), 576 GPUs (Rubin Ultra), and potentially over 1,000 GPUs with Feynman.

The "Copper Wall" vs. Optical Transition

> Copper is Staying Longer: Copper remains the preferred short-reach technology due to lower latency, lower power consumption, and lower cost. Innovations like PAM4/PAM6, advanced SerDes, and retimers are extending copper's life further than the industry previously expected.

> Optics is Inevitable but Back-Weighted: As cluster domains push past a single rack, managing electrical signal degradation at high speeds becomes too inefficient. Morgan Stanley expects Co-Packaged Optics (CPO) to see meaningful adoption starting with the NVIDIA Feynman generation around 2028–2029. Recent market sell-offs surrounding delayed CPO adoption are viewed as overdone.

Fabric & Ecosystem Protocol Debates

> NVIDIA Dominance: NVLink remains the dominant proprietary fabric. NVIDIA is also deploying NVLink Fusion, which allows third-party CPUs and custom ASICs to tie directly into the NVLink ecosystem.

> Open Alternatives Growing: Broadcom is spearheading Scale-Up Ethernet (SUE), while an AMD-led consortium is backing UALink as an open alternative. Morgan Stanley sees PCIe (e.g., via Astera Labs) acting as an important temporary bridge before hyperscalers migrate to native AI fabrics.

> AWS & Google Outliers: Google relies on an Optical Circuit Switch (OCS) Torus topology. AWS has shifted to a flatter, highly efficient mesh network called Resilient Network Graphs (RNG) using passive optics to reduce router counts and power consumption.

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