An AI cluster with 100,000 GPUs spends a meaningful fraction of its power budget just moving data between chips — not computing anything, just shuttling bits down copper and fiber. As clusters grow past that scale, the transceivers that convert electrical signals to light at the edge of every switch have become one of the biggest hidden costs in the building. Co-packaged optics is the industry's answer: stop converting signals at the faceplate and start converting them right next to the silicon that generates them.
It sounds like a small architectural tweak. It isn't. Moving the optical engine from a pluggable module a few inches away to a package sitting millimeters from the switch ASIC changes the power curve, the failure model, and the economics of building networks at datacenter scale. Nvidia, Broadcom, and most of the hyperscalers have all committed to it for next-generation systems, and 2025 was the year co-packaged optics stopped being a research demo and started shipping in production networking gear.
What Co-Packaged Optics Actually Is
Every high-speed network link eventually needs to leave the electrical domain and travel as light through fiber, because copper can't carry high-bandwidth signals more than a meter or two without unacceptable loss. The conversion happens in an optical transceiver: a small module that takes an electrical signal, drives a laser, and pushes light into a fiber (and does the reverse on receive).
In today's mainstream architecture, those transceivers are pluggable — physical modules like QSFP-DD or OSFP that plug into cages on the front panel of a switch, connected to the switch ASIC by several inches of copper trace and a retimer chip that cleans up the signal along the way.
Co-packaged optics (CPO) removes that separation. Instead of a pluggable module at the faceplate, the optical engines are mounted directly on the same substrate or package as the switch ASIC — often just millimeters away. The electrical signal travels a fraction of the distance before being converted to light, and it needs far less amplification and error correction to get there.
The Three Layers That Change
CPO isn't one component, it's a re-architecture of three things at once:
- The switch package — the ASIC and the optical engines share a substrate, connected by short, dense electrical traces instead of a printed circuit board trace running to the front panel.
- The optical engine — typically built with silicon photonics, using processes adapted from standard CMOS chip fabrication to put lasers, modulators, and waveguides on a chip.
- The fiber interface — light exits the package through fiber shuffles or ribbon connectors attached close to the switch, rather than through hundreds of individual pluggable modules racked along the switch's edge.
The result is a switch that looks and is serviced differently: fewer discrete parts, less board space dedicated to electrical signal integrity, and a fundamentally shorter electrical path.
Why This Matters Right Now
Nvidia's Spectrum-X Ethernet Photonics platform entered production as part of the Vera Rubin generation ramp — the clearest signal yet that co-packaged optics has moved from lab curiosity to a shipping component of mainstream AI infrastructure. Networking silicon that used to be a supporting act in GPU cluster design is now being engineered and marketed with the same urgency as the GPUs themselves.
That shift didn't happen because pluggable optics stopped working. It happened because the scale of AI training and inference clusters exposed costs that were tolerable at smaller scale and are not tolerable at hundreds of thousands of accelerators:
- Power per bit has become a capacity constraint. Datacenter power is now often the binding constraint on how many GPUs an operator can deploy, not capital or floor space. Every watt spent driving signals across a switch's front panel and through a retimer is a watt not available for compute.
- Link counts have exploded. Large AI training clusters interconnect GPUs with far more network bandwidth per accelerator than general-purpose cloud servers ever needed, multiplying the number of optical links (and therefore the transceiver power tax) many times over.
- Signal integrity gets harder at higher speeds. As per-lane data rates climb, the electrical trace between ASIC and pluggable module becomes a bigger source of signal loss, pushing designers toward more retiming stages — which themselves cost power and add latency.
Co-packaged optics attacks all three at once by shortening the electrical path to nearly nothing, which is precisely why the major switch silicon vendors are converging on it for their highest-end AI networking products rather than treating it as a niche option.
How It Works, Mechanically
At the heart of most CPO implementations is silicon photonics: using semiconductor manufacturing techniques, similar to those used for digital logic chips, to build optical components. A laser (often external, coupled in from a separate light source) feeds light into a waveguide etched on a silicon chip. Modulators encode electrical data onto that light by altering its phase or intensity. On the receive side, photodetectors convert incoming light back into electrical current.
What makes this "co-packaged" rather than just "silicon photonics" is the assembly step: the photonic integrated circuit (PIC) and the switch ASIC are packaged together, typically side by side on an interposer or substrate, connected by very short, high-density electrical interconnects instead of a board-level trace.
Pluggable vs. Co-Packaged: The Core Trade-off
| Dimension | Pluggable Optics | Co-Packaged Optics |
|---|---|---|
| Electrical path length | Several inches (PCB trace to faceplate) | Millimeters (within package) |
| Retiming stages needed | Typically multiple, for signal integrity | Minimal to none |
| Power per bit | Higher — retimers and longer traces cost energy | Lower — shorter path needs less drive power |
| Field serviceability | High — swap a failed module in seconds | Low — optical engine is soldered to the switch |
| Density (ports per rack unit) | Limited by faceplate space | Much higher — no faceplate cage constraint |
| Manufacturing maturity | Decades of volume production, mature supply chain | Early-stage, ramping through 2025–2027 |
| Risk on failure | Isolated to one module | Can affect optics tied to a whole switch package |
That serviceability trade-off is the crux of the debate inside networking teams: pluggables let you replace a bad transceiver during a maintenance window without touching the switch; co-packaged optics generally means the optical engine's fate is tied to the switch itself, which raises the stakes on manufacturing yield and long-term reliability.
Why Retiming Costs So Much
It's worth dwelling on why retimer chips matter so much to this power story. A retimer's job is to receive a degraded electrical signal, clean up its timing and amplitude, and pass along a crisp copy so the rest of the link doesn't accumulate errors. Every retiming stage adds a small, fixed amount of latency and a meaningful amount of power draw, because it's essentially a small signal-processing chip doing real work on every bit that passes through it. At the data rates modern AI fabrics run — well into the hundreds of gigabits per second per lane — a single link might need two or three such stages between the switch ASIC and the fiber. Multiply that by tens of thousands of ports in a large cluster, and retiming stops being a rounding error and becomes a line item. Shortening the electrical path is, in large part, a strategy for eliminating retiming stages altogether rather than merely making them more efficient.
Practical Implications for Businesses and Builders
For most software teams, this is infrastructure happening several layers below anything they'll touch directly. But for anyone making decisions about AI compute — buying capacity, building datacenters, or evaluating vendors — the shift has concrete consequences.
For Hyperscalers and Neoclouds
Operators building frontier-scale AI clusters are the primary adopters, because they're the ones for whom transceiver power and rack density genuinely gate how much compute they can stand up per megawatt of available power. For these buyers, co-packaged optics is a lever on cluster economics: fewer watts per bit means more GPUs behind the same power contract, and higher radix switches (more ports per package) mean fewer network tiers and less latency between GPUs.
For Enterprises Buying AI Capacity
Most enterprises will never spec a switch. But the underlying cost curve of the cloud AI capacity they rent is shaped by exactly this kind of infrastructure decision. Networking efficiency is one of the levers cloud providers pull to keep AI training and inference pricing competitive, alongside GPU generation and power procurement. Enterprises evaluating providers or negotiating long-term capacity commitments benefit from understanding that a chunk of the pricing story is being written in switch design labs, not just GPU roadmaps.
For Hardware and Systems Vendors
The transceiver and switch supply chain is being reorganized. Companies that built businesses around pluggable optics — module makers, connector manufacturers, retimer chip vendors — face a genuine strategic fork: invest in co-packaged silicon photonics capacity, specialize in a hybrid niche (linear pluggable optics that trade some power savings for serviceability), or cede the high end of the AI networking market. None of those are comfortable choices, and the next two to three years of vendor consolidation will likely be shaped by which bet each company made.
This also changes who systems integrators and datacenter operators need to talk to when they design a network. Historically, optics procurement was a largely separate conversation from switch procurement — buyers picked a switch vendor, then shopped a competitive, multi-vendor market for compatible pluggable modules. With co-packaged optics, the switch and the optics arrive as a single unit from a single vendor, which collapses that two-step procurement process into one and reduces the buyer's ability to mix and match on price. That's a meaningful shift in negotiating leverage that procurement teams at large AI infrastructure buyers are still adjusting to.
A Practical Checklist for Infrastructure Buyers
- Ask cloud or colocation providers directly what fraction of their AI cluster networking is pluggable vs. co-packaged, and on what roadmap that shifts.
- Weight power-per-bit claims against real serviceability data — CPO's efficiency gains are real, but so is the operational cost of a failed optical engine that takes a switch offline rather than a module.
- Treat network architecture as part of total cost of ownership conversations, not just GPU generation and count.
- For long-lead capacity planning, watch which switch silicon (and which optics approach) a provider is standardizing on for its next-generation clusters — it's a leading indicator of both price and available bandwidth per GPU.
Real Limitations and Open Questions
Co-packaged optics is not a solved problem being rolled out uniformly — it's an emerging architecture with real unresolved tensions.
- Repairability is a genuine regression. Pluggable optics turned a laser failure into a five-minute swap. Co-packaged optics, in most current implementations, ties the optical engine's failure mode to the switch package. Vendors are working on modular co-packaged designs that allow partial replacement, but none of the approaches match the simplicity of pulling a bad module.
- Manufacturing yield at scale is unproven. Packaging a photonic integrated circuit next to a large switch ASIC is a harder assembly problem than mounting a separate pluggable module. Yield losses on the combined package are more expensive than yield losses on a standalone transceiver, because you risk the whole switch, not just the optics.
- The external laser problem. Many silicon photonics designs still rely on an external laser source rather than one integrated on-chip, because on-chip lasers on silicon remain difficult to manufacture efficiently. That means a separate component (and separate failure mode) even in a "co-packaged" system — the industry hasn't fully closed this gap yet.
- Standardization is still forming. Pluggable optics benefit from decades of interoperability standards across vendors. Co-packaged optics implementations are more vendor- and platform-specific today, which raises switching costs and narrows the field of interchangeable suppliers for buyers.
- It doesn't fix the whole power problem. Optical interconnect efficiency addresses one layer of AI infrastructure's power appetite. GPU power draw, cooling, and power delivery upstream of the switch remain separate — and larger — problems that co-packaged optics doesn't touch.
These aren't reasons to dismiss the technology — the power and density gains are real and increasingly necessary — but they explain why adoption is concentrated at the highest end of AI infrastructure first, rather than spreading immediately across general-purpose datacenter networking.
What to Watch Next
The next 18–24 months will determine whether co-packaged optics becomes the default for all high-performance networking or stays a specialized tool for the largest AI clusters.
- Yield and reliability data from early production deployments. As Spectrum-X Ethernet Photonics and comparable Broadcom platforms accumulate field hours, real failure rates will either validate or complicate the technology's economics.
- Hybrid and modular approaches. Expect continued experimentation with designs that recover some of pluggable optics' serviceability — detachable optical engines, external laser modules that can be swapped independently of the switch package — as vendors try to close the repairability gap.
- Whether co-packaged optics moves beyond switches to accelerators themselves. The logical next step is co-packaging optical I/O directly with GPU or accelerator packages, not just networking switches, which would push optical interconnects even closer to the compute itself.
- Price and power disclosures from cloud providers. As co-packaged optics reaches production scale, watch for cloud and neocloud providers to start citing network efficiency explicitly in capacity and pricing communications, the way they already cite GPU generation.
- Competitive response from pluggable optics vendors. Linear-drive pluggable optics (which remove some retiming stages without going fully co-packaged) are a credible middle path, and their commercial traction will indicate how much of the market actually needs the full co-packaged jump.
FAQ
What is co-packaged optics in simple terms?
It's a way of building network switches where the components that convert electrical signals into light are mounted directly next to the switch chip, instead of plugging into modules on the front panel. This shortens the electrical path a signal has to travel, which saves power and improves signal quality.
Why are AI datacenters adopting co-packaged optics now?
AI training clusters use far more network bandwidth per chip than typical cloud servers, and power has become the main constraint on how much compute operators can deploy. Co-packaged optics reduces the power spent moving data between switches, freeing up capacity for actual compute. Nvidia's Spectrum-X Ethernet Photonics entering production alongside the Vera Rubin ramp is a concrete example of this shift reaching commercial scale.
Is co-packaged optics the same as silicon photonics?
No, they're related but distinct. Silicon photonics is the underlying manufacturing approach — building optical components using semiconductor fabrication techniques. Co-packaged optics is an assembly and system-design choice: packaging those photonic components physically next to the switch ASIC rather than in a separate pluggable module.
What's the biggest downside of co-packaged optics?
Serviceability. A failed pluggable transceiver can be swapped in minutes without touching the switch. In most co-packaged designs, the optical engine is soldered into the same package as the switch, so a failure is harder and more disruptive to fix.
Will co-packaged optics replace pluggable transceivers everywhere?
Not immediately, and possibly not ever completely. It's being adopted first at the highest end of AI networking, where power and density gains matter most. General-purpose enterprise networking, where serviceability and vendor interoperability matter more than squeezing out every watt, will likely keep using pluggable optics for years.
Does co-packaged optics reduce latency as well as power?
Yes, though power savings get more attention. Shorter electrical paths and fewer retiming stages also reduce the time it takes a signal to traverse the switch, which matters for AI training workloads that are sensitive to network latency across large GPU clusters.
Which companies are leading in co-packaged optics for AI networking?
Nvidia and Broadcom are the most prominent names shipping co-packaged optics platforms for AI datacenter switches as of late 2025, alongside a broader ecosystem of silicon photonics and packaging specialists supplying components into their platforms.
Teams evaluating AI infrastructure decisions shaped by this shift can get hands-on help from Woyce Technologies.