Micron Delivers Industry’s Highest Capacity SOCAMM2 for Low-Power DRAM in the AI Data Center
Shannon Davis
2 days ago
In an era of unprecedented AI innovation and growth, the entire data center ecosystem is transforming toward more energy-efficient infrastructure to support sustainable growth. With memory playing an increasingly critical role in AI systems, low-power memory solutions have become central to this transformation.
Micron Technology, Inc. (Nasdaq: MU) today announced customer sampling of 192GB SOCAMM2 (small outline compression attached memory modules) to enable broader adoption of low-power memory within AI data centers. SOCAMM2 extends the capabilities of Micron’s first-to-market LPDRAM SOCAMM, delivering 50% more capacity in the same compact footprint. The added capacity can significantly reduce time to first token (TTFT) by more than 80% in real-time inference workloads. The 192GB SOCAMM2 uses Micron’s most advanced 1-gamma DRAM process technology to deliver greater than 20% improvement in power efficiency, further enabling power design optimization of large data center clusters. These savings become quite significant in full-rack AI installations, which can include more than 40 terabytes of CPU-attached low-power DRAM main memory. The modular design of SOCAMM2 improves serviceability and lays the groundwork for future capacity expansion.
Building on a five-year collaboration with NVIDIA, Micron pioneered the use of low-power server memory in the data center. SOCAMM2 delivers LPDDR5X’s inherent advantages — exceptionally low power consumption and high bandwidth — to the main memory of AI systems. Designed to meet the evolving demands of massive-context AI platforms, SOCAMM2 provides the high data throughput required for AI workloads while delivering new levels of energy efficiency, setting a new standard for AI training and inference systems. This combination of advantages will make SOCAMM2 a key memory solution for leading-edge AI platforms in the years ahead.
“As AI workloads become more complex and demanding, data center servers must achieve increased efficiency, delivering more tokens for every watt of power,” said Raj Narasimhan, senior vice president and general manager of Micron’s Cloud Memory Business Unit. “Micron’s proven leadership in low-power DRAM ensures our SOCAMM2 modules provide the data throughput, energy efficiency, capacity and data center-class quality essential to powering the next generation of AI data center servers.”
Through specialized design features and enhanced testing, Micron SOCAMM2 products transform low-power DRAM, initially designed for mobile phones, into data center-class solutions. Extensive experience in high-quality data center DDR memory helps Micron ensure that SOCAMM2 meets the stringent quality and reliability requirements of our data center customers.
SOCAMM2 improves power efficiency by more than two-thirds4 compared with equivalent RDIMMs, while packing its performance into a module one-third the size5, optimizing data center footprint and maximizing capacity and bandwidth. SOCAMM’s modular design and innovative stacking technology improves serviceability and aids the design of liquid-cooled servers.
Micron has been an active participant in the JEDEC SOCAMM2 specification definition and is working closely with industry partners to drive standards that will accelerate low-power adoption in AI data centers to improve power efficiency across the entire industry. SOCAMM2 customer samples are shipping now in capacities up to 192GB per module and speeds up to 9.6 Gbps, with high-volume production aligned to customer launch schedules.
Copilot:
Absolutely—SOCAMM2 has the makings of a breakout memory format, especially for AI inference and high-density server deployments. Here’s why it could be a real winner:
What Makes SOCAMM2 Stand Out
- 192GB capacity per module: That’s massive—ideal for LLM inference, agentic AI, and memory-bound workloads.
- Micron’s 1? DRAM node: Offers >20% power efficiency and >30% density gain over 1ß, giving SOCAMM2 a serious edge in both performance and cost-per-bit.
- Serial memory architecture: Reduces pin count and improves signal integrity, especially at high speeds (up to 9200 MT/s).
- Form factor: SOCAMM2 is thinner and more thermally efficient than traditional RDIMMs, making it attractive for dense server racks and accelerators.
Competitive Landscape
- CAMM2 (JEDEC standard) is gaining traction in laptops and some servers, but SOCAMM2 is optimized for data center inference, not client devices.
- HBM3E and CXL.mem are alternatives, but they’re more expensive and complex to integrate. SOCAMM2 hits a sweet spot between capacity, bandwidth, and cost.
- Samsung’s 1c DRAM—its closest rival—is still undergoing redesign due to yield and size issues, giving Micron a clear lead in execution.
Strategic Implications
- SOCAMM2 could become the go-to memory format for inference accelerators, especially in systems that don’t need full HBM stacks but still demand high bandwidth and capacity.
- If paired with chips like Groq, D-Matrix, or VSORA’s Jotunn8, it could enable lower-latency, higher-throughput inference at lower power.
Bottom line: SOCAMM2 is poised to disrupt the memory hierarchy—not by replacing HBM, but by offering a scalable middle ground that’s perfect for the AI inference boom. If you want to compare SOCAMM2’s thermal profile or layout density vs CAMM2 or RDIMM, I can break that down next. |
