AVGOBroadcom Inc.

“when I say we forecast, we have a line of sight that our revenue in '27 will be significantly in excess of $100 billion. I'm focusing on the fact that these are pretty much all based on chips, whether they are XPUs, whether they are switch chips, DSPs, these are silicon content we're talking about.”

“Q1 AI networking revenue grew 60% year-on-year and represented 1/3 of total AI revenue. In Q2, we project AI networking to accelerate a lot more and grow to 40% of total AI revenue.”

“Our custom accelerator business grew 140% year-on-year in Q1. This momentum continues in Q2. The ramp of custom AI accelerators across all our 5 customers is progressing very well.”

“For Anthropic, we are off to a very good start in 2026 for 1 gigawatt of TPU compute. And for '27, this demand is expected to surge in excess of 3 gigawatts of compute.”

“We also now have a sixth customer. We expect OpenAI deploying in volume their first-generation XPU in 2027 at over 1 gigawatt of compute capacity.”

“today, in fact, we have line of sight to achieve AI revenue from chips, just chips, in excess of $100 billion in 2027.”

“AI semiconductor revenue, which grew 106% year-on-year to $8.4 billion, way above our outlook.”

“AI revenue growth, which will accelerate very sharply to 140% year-on-year to $10.7 billion.”

“if you look at it by gigawatt in '27, we are seeing it getting close to 10 gigawatts.”

“contrary to recent analyst reports, Meta's custom accelerator MTIA road map is alive and well. We're shipping now. And in fact, for the next-generation XPUs, we will scale to multiple gigawatts in '27 and beyond.”

“For Google, we continue our trajectory of growth in '26 with strong demand for the seventh-generation Ironwood TPU. In 2027 and beyond, we expect to see even stronger demand from next generations of TPU.”

“our first-to-market Tomahawk 6 switch at 100 terabit per second as well as our 200G SerDes are capturing demand from hyperscalers, whether they use XPUs or GPUs this year.”

“I expect as a composition of our total AI revenue in any quarter that will be ranging between probably 33% to 40% AI networking components.”

“Most of our customers begin with inference simply because that tends to be the easiest path to start on, not necessarily from anything else than the fact that, when you do inference, it's much -- it's less compute. But also then the question is, do you need this general purpose, massive dense matrix multiplication GPUs when you can do it more efficiently, effectively with customs inference silicon XPUs that do the job better or just as well, much cheaper cost, lower power.”

“The one size fits all of a general purpose GPU gets you only that far. It can still keep going on because you can still run different workloads, like you run mixture of experts, even though you have -- you want to run mixture of experts with [ sparse costs ] to be very effective, you hear the term, but in a GPU, you're designed for dense matrix multiplication.”

“VMware Cloud Foundation, VCF, is the essential software layer in data centers integrating CPUs, GPUs, storage and networking into a common high-performance private cloud environment. As the permanent abstraction layer between AI software and physical chips, silicon, VCF cannot be disintermediated or replaced.”

“we're also seeing very rapidly more for those customers who are much more matured in the progression I talked about in their journey towards complete XPU, that they will start to develop 2 chips each year simultaneously, one for training, one for inference to be specialized.”

“We bring to the partnerships, each of them, unmatched technology in SerDes, silicon design, process technology, advanced packaging and networking to enable each of these customers to achieve optimal performance for their differentiated LLM workloads.”

“We've been doing this for 20 years, more than 20 years in silicon. And in this particular space today in generative AI, if you're trying to, as an LLM player, to do your own chip, you cannot afford to have a chip that is just good enough.”

“we build custom silicon for 6 customers. We have very deep strategic multiyear engagement with them. They share with us because of this custom capability exactly what they anticipate at least over the next 2 to 3 years, sometimes 4 years.”

“what is very, very interesting and surprising too to us is very much for inference in order to productize the LLMs, their latest LLMs they create and monetize it. And that inference is driving a substantial amount of compute capacity”

“we can push the envelope from 100G to 200G to even 400G. We have SerDes now running 400G that can drive distance on a rack to run copper.”

“a lot of the XPU designs we're doing, we're being asked to scale-up through Ethernet, and we're happy to enable that.”

“we have fully secured capacity of these components for '26 through '28.”

“To them, as to every one of my customers in this space, it's a strategic play. It's not optionality. To them, long term, short term, medium term is strategic, extremely strategic.”

“we will not see competition in COT for many years to come. It will come eventually, but we're still a long way off because the race which we see continues.”

“We are confident that the growth in generative and agentic AI will create the need for more VMware, not less.”

“our business in XPUs is a strategic sustainable play for all the 6 customers we have today.”