The newly named D-Series GPU has up to 480GB of LPDDR5X memory, 1.5TB/s of memory bandwidth
Intel rates it for up to 1.3 PetaFLOPS of FP8 performance, with support for formats ranging from FP4 to FP64. It features a total of 32 Xe3P cores, 256 XMX engines, 32 MB of unified L2 cache.
No cost estimates currently, I hope they launch a generic blower style variant at a later date for prosumer workstations.
Intel GPU D-Series Specifications
Intel GPU D270
**Xe Cores**
32
**XMX Engines**
256
**GPU Clockspeed**
~2.5GHz
**Peak Matrix Throughput (FP8)**
1.3 PFLOPS
**Peak Vector Throughput (FP64)**
10.2 TFLOPS
**Memory (Max)**
480GB LPDDR5X (ODMs), 160GB LPDDR5X (Intel)
**Memory Bandwidth**
1.5TB/sec (~9375Mbps x 1280-bits)
**ECC**
Yes
**L2 Cache**
32MB
**I/O**
PCIe Gen5 x16
**TDP**
350W
**Form Factor**
PCIe CEM (Air Cooled)
**Architecture**
Xe3P
**GPU**
Crescent Island
Edit: Memory bandwidth added to the description, added a table via STH.
I looked up current prices and this does seem like an accurate estimate, assuming they can get the chips itself made for 1,000$ and with a 10% markup a 10,000$ gpu would be highly price competitive atm. Im sure they would love a 70% markup though.
At 10k or even 12k, It actually looks quite compelling next to a 20k RTX 6000 pro. Cause realistically you still dont have enough VRAM with 96GB for the really interesting models.
Cant wait to get my hands on these for a decent price in 10 years lol.
It's like 4 dgx sparks so anything under $25K isn't bad. I'd be all over $10K. Hell, if I can get it for something close to an rtx pro 6000, I will. I bet it could do well w/DS 4.1 flash.
Honestly, I'm just excited to see something like this that me a lowly consumer will even see a number without having to ask for a quote. I doubt I'll be able to afford it, but it's nice to see. I'll of course be disappointed if that's not the case.
There are many Intel Gaudi 2 servers with 8x 96GB gpus for 15-20k$. Each has 2.5TB/s bandwidth and 400TFlops of bf16/fp16. That's 2000$ per 96GB gpu. I just can't find them selling the gpu's standalone and there are no adapters yet. Yes that's not cheap but it's much cheaper than RTX 6000 that's 16-20k alone right now.
This is still a risky proposition for now but within a year who knows, I'd be open to going in on one with a few folks and throwing some tokens at it. I just dont want a 20k paperweight. A 4k paperweight I can deal with.
It depends on preexisting work. I.e. I've spent just $5 on DeepSeek 4.1 Flash porting GGML kernels into newest vllm for Mi50; in result, got vllm running q8 ggufs 30% faster than llama.cpp did. Intel has some support here and there too; so if they would sell me a 100gb GPU for like $1500, I'd totally do it.
This is definitely a problem for hyperscalers with their complicated training pipelines, but not really for us. Just throw one "claude modify vllm kernel to run on intel gaudi 2 arch, make no mistakes" on it and let it run for a day or two. The hard part is actually connecting it to a motherboard. So far only Volta SXM boards have very good support with nvlink working, but anything newer has nothing right now. There are even Amd mi250x chips selling standalone with 128GB of hbm for just 2-3k, but still no PCBs to mount them to.
I was actually pleasantly surprised with llama.cpp / SYCL and Intel one api - if all you want to do is run LLM inference then these will be decent. Running pytorch models, training and what not, its not impossible but more difficult than CUDA for sure.
But we also live in a world where you can let point Claude to a pytorch impl of some obscure model and it will make you a ggml/gguf version + quants + optimize it for whatever hardware you have. If you dont believe me, try it! I think its the LLM agents that will remove the CUDA barrier eventually, as Nvidia is taking legal action against any CUDA copycat projects.
It appears to me as 100Gb/s link speed or PCIE 4x16.. I stopped looking though.
It's going on 5 years old at this point. I don't think it is selling because most consumers want the latest tech and businesses don't look for these kinds of opportunities because they have no supply chain reliability. So it's a economic opportunity if you have $20k lying around for a hobbiest inference box.
I run about 200 of those at ASU, for our local campus inference, they are a good deal, and luckily the VLLM Gaudi project has really picked up pace these last few months. Each averages about 2500 watts.
I have been able to get most of the popular models working at this point, most with just ok speeds but lots of capacity. Currently pushing around 40B tokens per week at about 50% utilization. Most popular models are glm 5.3 and 5.3 Flash, deepseek v4.1 flash and qwen 3.8 27b
Yeah, this is the type of product we need for when the rampocalypse ends. Much easier to plug that 350W PCI-E card, even if one needs a 3D-printed fan shroud, compared with multi-kW liquid cooled compute modules on proprietary base boards.
And locally more RAM at decent bandwidth is usually much more valuable than less high speed HBM.
Consumer Arc is dead as expected but I'm glad they haven't given up on Arc.
Can someone freeze me for 20 years so I can afford to buy one of these used?
i think for local llama the holy grail is one of these 128gb cpus. its not super fast but will do everything and you can get some large models on there. local guy isn't hosting a million transactions like datacenters do so a being slow isn't that much of a problem. getting flexibility to try larger models is where its at imo
Especially when AMD Medusa Halo doubles the RAM bandwidth to above 400GB/s (possibly as high as 691GB/s)! Having that at PC (vs Mac) prices will be revolutionary, if RAMpocalypse ever ends. I think AMD will conquer the local inference for small-medium business market as well, with that kind of product. Intel should take note and also add more RAM channels to their consumer chips.
If you’re okay with 200GB or so of memory bandwidth, a gen 3 Epyc and ddr4 are a decent way to make that happen - gotta be one of the 8 channel cpus. 16gb ddr4-3200 rdimms are relatively cheap compared to 32 or 64 gig sticks. You can prob still do a motherboard, cpu, and 128gb of memory for $2000 or so. Side benefit is you can add GPUs later if you’d like.
1.5tb/s? Blackwell pro is 1.8. That bandwidth can support 50+ t/s on any model that will fit in it. And that's the level your Claude or openai subscription works at.
Not for local AI (this does not have a fan of its own and can't easily be put in a regular PC case).
Price is guaranteed to not be cost competitive for non-datacenters.
Also it uses LPDDR5X, so this hardly counts as VRAM, this is just regular RAM on the GPU (better than CPU inference but damn) lol.
Assuming it can undercut the competition by releasing for 20K (I doubt it) for the 480GB version, you're better off getting an entire M5 studio, which gives you more memory and lower energy consumption, probably faster real-world speeds too. Update: For everyone talking about the bus, the M5's bus is 1.2TB/s. My comparison stands.
Still amazed that unfortunately most manufacturers still lack the technical know-how and immense resources required to figure out how GPU shrouds with squirrel fans work. Unfortunately it takes a trillion dollar company to pull something like that off.
RAM on a GPU is referred to as VRAM, doesn't matter what kind it is. I expect this to still have a gigantic memory bandwidth, probably went with LPDDR5 because it's cheaper than GDDR.
Depends on no. of channels/bus width. lpddr can be relatively high bandwidth. However at 350W, it's probably not above 1.2tb/s is my theoretical max educated guesstimate, we'll be lucky if it's above 200gb/s
Wait I'm realising that I assumed the full memory configuration. Perhaps the 160gb works fine with 350W. The 400gb+ cards are gonna eat power at idle tho lol
LPDDR5X@ ~9375Mbps x 1280-bits bus. 5090 for example has only like 512bit wide bus on GDD7, and a typical home PC has DDR5 64bit (2x32bit Dual Channel). GDDR trades latency for more bandwidth.
Kind of reminds me of the PlayStation 2, where it's "GPU" has 2560-bit bus for memory, so a 4MB VRAM has like 48GB/s of bandwidth, ridiculously high for 2000 hardware.
If they just made a subwide bus to connect to all LPDDR5X in parallel then it can still be miles better than regular desktop DDR5. They do claim 1.5TB/s, thats decent bandwidth regardless of the memory type used here and definilty GPU territory. RTX 5090 or RTX 6000 pro also have 1.7TB/s, so it would be comparable.
The only way you get high bandwidth with lpddr5x is to increase the bus width. Considering the capacity we are talking about i suspect that unless you have the fully populated version of the card all the smaller versions will have nerfed bandwidth
Nope. Not even close. But I’m pretty good at marketing and am therefore skeptical.
“…comparing different architectures based on theoretical throughput alone rarely pans out in the real world, so a lot of the GPU’s competitiveness is going to hinge on its overall architectural efficiency…”
“…The company’s own card will ship with 160GB of LPDDR5X memory…”
“…At this point the company has all but fully revealed its specifications and theoretical performance – now it is just a matter of when it will ship, and how much Intel will charge for it….”
Sorry but you are poorly informed. No need for marketing.
You can get plenty of bandwidth out of LPDDR by making bus width larger, i.e. 1024 bit vs 128 bit or 96 bit that you might see on a cell phone.
LPDDR is going to be used much more broadly in data center applications going forward because of its efficiency and cost. It scales just fine to higher bandwidth requirements. Nothing fundamentally low bandwidth about LPDDR.
I honestly wish and pray for the day the US government incentivizes its people over oligarchs.
Like do these people not understand that normal people, and not hyperscalers need to adopt to this new technology in order for this shit to remotely be integrated into our lifestyle.
I see a dotcom type button x100 on this which can easily be solved if greed wasn’t such a god damn problem.
It’s nasty. Granted, there is B60/70 or R9700 but someone seriously needs to spank Nvidia for being this greedy.
You spew nonsense. This is supply and demand in action. I don't care for ai companies overpaying for hardware and screwing over my hardware purchases either, but markets are working how they are supposed to in the situation. Or are you saying you want the US government to price freeze ram made overseas so you can build a gaming PC? Next you'll tell me price freezes can be implemented for oil globally because you want $1/gallon, the world owes it to you.
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u/--Spaci-- 8h ago
Sounds nice, I doubt it will be a reasonable price though!