Given the price of these systems the ridiculously expensive network cards isn't such a huge huge deal, but I can't help but wonder at the absurdly amazing bandwidth hanging off Vera, the amazing brags about "7x more bandwidth than pcie gen 6" (amazing), but then having to go to pcie to network to chat with anyone else. It might be 800Gbe but it's still so many hops, pcie is weighty.
I keep expecting we see fabric gains, see something where the host chip has a better way to talk to other host chips.
It's hard to deny the advantages of central switching as something easy & effective to build, but reciprocally the amazing high radix systems Google has been building have just been amazing. Microsoft Mia 200 did a gobsmacking amount of Ethernet on chip 2.8Tbps, but it's still feels so little, like such a bare start. For reference pcie6 x16 is a bit shy of 1Tbps, vaguely ~45 ish lanes of that.
It will be interesting to see what other bandwidth massive workloads evolve over time. Or if this throughout era all really ends up serving AI alone. Hoping CXL or someone else slims down the overhead and latency of attachment, soon-ish.
From the "fridge purpose-built for storing only yellow tomatoes" and "car only built for people whose last name contains the letter W" series.
When can this insanity end? It is a completely normal garden-variety ARM SoC, it'll run Linux, same as every other ARM SoC does. It is as related to "Agentic $whatever" as your toaster is related to it
So does this cut out Intel/x86 from all the massive new datacenter buildouts entirely? They've already lost Apple as a customer and are not competitive in the consumer space. I don't see how they can realistically grow at all with x86.
I'm assuming this is for tool call and orchestration. I didn't know we needed higher exploitable parallelism from the hardware, we had software bottlenecks (you're not running 10,000 agents concurrently or downstream tool calls)
Can someone explain what is Vera CPU doing that a traditional CPU doesn't?
What the heck is agentic inference and how is it supposed to be different from LLM inference? That's a rhetorical question. Screw marketing and screw hype.
Are we rapidly careening towards a world where _only_ AI “computing” is possible?
Wanted to do general purpose stuff? Too bad, we watched the price of everything up, and then started producing only chips designed to run “ai” workloads.
Oh you wanted a local machine? Too bad, we priced you out, but you can rent time with an ai!
Feels like another ratchet on the “war on general purpose computing” but from a rather different direction.
This is the related benchmark blog from Redpanda [disclosure: I work for Redpanda and I helped write this. Credit to Travis Downs & others at Redpanda for the heavy lifting on the testing and analysis.]
Ahhh, so is this a chip "more optimised" for connecting GPU's to reality ... or are they skipping the GPU step entirely? Are GPU's only for training now?
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[ 2.7 ms ] story [ 54.3 ms ] threadI keep expecting we see fabric gains, see something where the host chip has a better way to talk to other host chips.
It's hard to deny the advantages of central switching as something easy & effective to build, but reciprocally the amazing high radix systems Google has been building have just been amazing. Microsoft Mia 200 did a gobsmacking amount of Ethernet on chip 2.8Tbps, but it's still feels so little, like such a bare start. For reference pcie6 x16 is a bit shy of 1Tbps, vaguely ~45 ish lanes of that.
It will be interesting to see what other bandwidth massive workloads evolve over time. Or if this throughout era all really ends up serving AI alone. Hoping CXL or someone else slims down the overhead and latency of attachment, soon-ish.
Maia 200: https://www.techpowerup.com/345639/microsoft-introduces-its-...
From the "fridge purpose-built for storing only yellow tomatoes" and "car only built for people whose last name contains the letter W" series.
When can this insanity end? It is a completely normal garden-variety ARM SoC, it'll run Linux, same as every other ARM SoC does. It is as related to "Agentic $whatever" as your toaster is related to it
Can someone explain what is Vera CPU doing that a traditional CPU doesn't?
Seems like a triumph of hype over reality.
China can do breathless hype just as well as Nvidia.
Wanted to do general purpose stuff? Too bad, we watched the price of everything up, and then started producing only chips designed to run “ai” workloads.
Oh you wanted a local machine? Too bad, we priced you out, but you can rent time with an ai!
Feels like another ratchet on the “war on general purpose computing” but from a rather different direction.
(Could be both)
So they make inference cheaper and the models get even worse. Or Jensen Huang has AI psychosis. Or both.
Here is a new business idea for Nvidia: Give me $3000 in a circular deal which I will then spend on a graphics card.
https://www.redpanda.com/blog/nvidia-vera-cpu-performance-be...
It’s a CPU designed for an AI cluster. Their last CPU Grace was the same thing and no one called it agentic.
Vera now just has more performance/more bandwidth. It’s cool, I’d like to have one of these clusters, but this is not new.
It’s marketed as agentic AI because that’s fashionable in 2026.