You can tell by the shape of the board that it's meant to go into a server chassis behind a stack of 80mm blower fans. It's not meant for consumers, but you will be able to buy it used for $200 off ebay in 7 years to put in your home lab.
Intel ai gpu division is so aggressively anti “small” consumer. I think it has something to do with low volume and a small sales/distribution network. The data center cards I have from amd and nvidia are grey market at best. I don’t think intel moved enough units to establish alternate channels.
What I don't understand is: when you only plan for your product to have 10 customers, why even make a marketing page like this for it? At that point it's essentially the hardware equivalent of consultingware, something you sell to your existing contacts through outbound calls and by shoving ads through the B2B equivalent of a post-consumer sales channel (i.e. proactive outreach by your org's internal champion for that customer, to said customer.)
Looks like Intel is choosing to title its new crescent island cards with the D prefix despite being Crescent Island.
Kind of disappointed that Intel is (probably) not going to release consumer class GPUs. Intel's driver stack was seriously getting mature—both on Linux and Windows. It's always nice to have a third option available.
For now. A limited run of Celestials until 2028 when Serpent Lake switches to Nvidia tiles, and a bit longer for the LTS combo (AMD style) IO+GPU die in lower end/embedded products.
Druid is still dead, consumer DGPUs are still, and workstation DGPUs also seems to be dead, and most of the Xe driver team for Windows was laid off, as well as most of the Xe chip design team.
They originally said it was going to be 120GB but that partners could ship bigger capacities. So much for that!
I do hope this has a price point that makes it somewhat competitive with a Mac! Consumers have had nearly no choices available for mem capacity, and 20 channels of lpddr5 is one way to get that capacity! Go Intel!
Both this GPU and the Mac are constrained by a lack of GPU compute. There's basically no rack-scale GPUs with 480gb on-die that have a sub-400W compute element. It's going to be incredibly prefill-constrained on denser model inference just like the Apple Silicon iGPUs are.
> But I am surprised that they were able to pack so much flops into 300W.
I'm not. When you're doing inference you typically reduce power limits anyway if you're optimizing for efficiency. Even if you don't, it doesn't spike to the max of the card.
My 3090 I power it down to 175W or so for single-digit reductions in performance for like, 60% of the wattage, something like that.
> Efficient token serving
Dense, air-cooled, standard PCIe infrastructure helps maximize tokens per rack and watt, scaling serving capacity and keeping costs in check.
Next the tokens will be asking for tequila and caviar. Bow down to the new token overloads.
With an impressive 1.5TB/s RAM bandwidth you'd think they'd advertise that more.
Marketing department asleep at the wheel.
Fun to see the LLMism on the product page: "A, not B"
Can I actually buy this? Should I prefer it over Blackwell?
You can tell by the shape of the board that it's meant to go into a server chassis behind a stack of 80mm blower fans. It's not meant for consumers, but you will be able to buy it used for $200 off ebay in 7 years to put in your home lab.
> Can I actually buy this?
No. Certainly not now, maybe not ever. That is the least consumer-focused product page I've seen today.
Intel ai gpu division is so aggressively anti “small” consumer. I think it has something to do with low volume and a small sales/distribution network. The data center cards I have from amd and nvidia are grey market at best. I don’t think intel moved enough units to establish alternate channels.
Serious question, would they bother?
You can work with 10 players that will buy all of them with minimal effort.
What I don't understand is: when you only plan for your product to have 10 customers, why even make a marketing page like this for it? At that point it's essentially the hardware equivalent of consultingware, something you sell to your existing contacts through outbound calls and by shoving ads through the B2B equivalent of a post-consumer sales channel (i.e. proactive outreach by your org's internal champion for that customer, to said customer.)
Seems incredibly little compute for this. Is it meant to be MoE specific?
How many fps in Cyberpunk 2077?
Can It Run Crysis?
Yay more vaporware hardware I get to read about and never see or have a chance to buy.
This stuff you usually buy second hand in 6 years when the data centers get rid of them.
Ai generated no doubt
Looks like Intel is choosing to title its new crescent island cards with the D prefix despite being Crescent Island.
Kind of disappointed that Intel is (probably) not going to release consumer class GPUs. Intel's driver stack was seriously getting mature—both on Linux and Windows. It's always nice to have a third option available.
Its wild to me that intel isnt trying significantly harder on gpus
Theres so much money to be made
At least that driver stack will continue to mature?
On Linux mainly, and almost strictly for compute workloads (not much need to optimize for 3D workloads given the customer base).
They're still using Xe based iGPUs, so 3D still matters.
For now. A limited run of Celestials until 2028 when Serpent Lake switches to Nvidia tiles, and a bit longer for the LTS combo (AMD style) IO+GPU die in lower end/embedded products.
Druid is still dead, consumer DGPUs are still, and workstation DGPUs also seems to be dead, and most of the Xe driver team for Windows was laid off, as well as most of the Xe chip design team.
They originally said it was going to be 120GB but that partners could ship bigger capacities. So much for that!
I do hope this has a price point that makes it somewhat competitive with a Mac! Consumers have had nearly no choices available for mem capacity, and 20 channels of lpddr5 is one way to get that capacity! Go Intel!
Both this GPU and the Mac are constrained by a lack of GPU compute. There's basically no rack-scale GPUs with 480gb on-die that have a sub-400W compute element. It's going to be incredibly prefill-constrained on denser model inference just like the Apple Silicon iGPUs are.
This GPU has 1.3 PFLOPS of FP8 compute performance and 1.5 TB/s of memory bandwidth: https://videocardz.com/newz/intel-gpu-d270-is-xe3p-crescent-...
This is almost twice better than RTX 5090. This GPU will not be prefill constrained, I feel.
But I am surprised that they were able to pack so much flops into 300W.
> But I am surprised that they were able to pack so much flops into 300W.
I'm not. When you're doing inference you typically reduce power limits anyway if you're optimizing for efficiency. Even if you don't, it doesn't spike to the max of the card.
My 3090 I power it down to 175W or so for single-digit reductions in performance for like, 60% of the wattage, something like that.
It seems like there’s a market out there that is just happy to run the models locally, even if generation is slow.
Am I wrong to assume that large MoE models are likely the point anyway? Seems like this card would love DeepSeek V4.1 Flash.
> Efficient token serving Dense, air-cooled, standard PCIe infrastructure helps maximize tokens per rack and watt, scaling serving capacity and keeping costs in check.
Next the tokens will be asking for tequila and caviar. Bow down to the new token overloads.