Micas Bailly, a 51.2T co-packaged optics switch on Broadcom's Tomahawk 5 Bailly platform, is OSPA 1.0 Aligned. 70% lower optical power. In mass production.
LPO, NPO and CPO are three ways to place the optics in a data center switch. Linear pluggable optics (LPO) remove the signal processor from front-panel modules. Near-packaged optics (NPO) move the optics next to the switch chip. Co-packaged optics (CPO) put them inside the chip package. In Micas testing, CPO cut switch power by over 50%.
AI data centers are running into a wall, and it isn't compute. It's the power and space it takes to move data between switches. A CPO switch puts its optical engines inside the same package as the switch chip, instead of in plug-in modules on the front panel. This plain-language guide covers how co-packaged optics works and why it saves more than 50% of switch power. It also covers the reliability tradeoffs and how the Micas 51.2T CPO switch got into volume production.
Company-operated manufacturing and clean-room capability support one of the industry's first commercially available CPO switches, available now through Supermicro
Micas is taking ownership of AI infrastructure further. The Open AI Factory brings networking, transceivers, compute, and factory-owned integration together into one validated solution built for performance, availability, power efficiency, interoperability, and greater control from day one.
AI infrastructure performance means little without availability. Learn how redundancy, validated interoperability, qualified alternates and supply-chain resilience can keep AI factories running when components fail.
Open networking is mainstream—but if your network is open, why should your optics be locked down? See how Micas brings SONiC, multi-vendor optics, and validated interoperability together for the Open AI Factory.
The AI-cluster optics market reached $16.5 billion in 2025 and is on track to hit $26 billion in 2026 — roughly 60% growth for two years running. A market that doubles in two years isn’t a refresh cycle. It’s a structural shift in how AI infrastructure is engineered.
Spine–leaf buildouts with validated 400G short-reach optics deliver AI-grade bandwidth, port density, and cost-per-bit economics enterprises can actually afford — on open, multi-vendor fabrics.
Distributed training runs across a network of GPUs that exchange gradients, activations, and weights constantly. That network is the scale-out fabric — and at its physical layer sit optical transceivers, converting electrical signals to light and back on every link. The transceiver is not a commodity accessory. It is the physical layer of every GPU cluster. Slow, unreliable, or incompatible optics leave GPUs idle waiting for data — and idle GPUs are the most expensive asset in a data center. Seriously. They cost upwards of $30,000 and that is if you can even get one.