I have no idea of the likely price, but (IMO) this is the sort of disruption that Intel needs to aim at if it's going to make some sort of dent in this market. If they could release this for around the price of a 5090, it would be very interesting.
LPDDR5x really just means LPDDR5 running at higher than the original speed of 6400MT/s. Absent any information about which faster speed they'll be using, this correction doesn't add anything to the discussion. Nobody would expect even Intel to use 6400MT/s for a product that far in the future. Where they'll land on the spectrum from 8533 MT/s to 10700 MT/s is just a matter for speculation at the moment.
160 GB LPDDR5 is ~$1,200 retail so the card could be sold for $2,000. The price will depend on how desperate Intel is. Intel probably can't copy Nvidia's pricing.
Uncle Sam owns a good chunk of Intel now. "Not affordable by civilians" might be precisely the target market: the DoD/national intelligence agencies have money to burn, can fund things long enough to stabilize Intel a little, and in exchange they get first dibs on everything.
Xe3P as far as I remember is built in their own fabs as opposed to xe3 at TSMC. This could give them a huge advantage by being possibly the only competitor not competing for the same TSMC wafers
Funny they still call them graphics cards when they're really... I dont know, matmul cards ? Tensor cards ? TPU ?
Well that sums it up maybe, what those are are really CUDA cards.
Dude, this is asinine. Graphics cards have been doing matrix and vector operations since they were invented. No one had a problem with calling matrix multiplers graphics cards until it became cool to hate AI.
Yes. The earliest consumer PC 3D graphics cards just rasterized pre-transformed triangles and that's it; the CPU had to do pretty much all the math (but drawing the pixels was considered the hard part). Later, "Hardware Transform and Lighting (T&L)" was introduced circa 2000 by cards like the GeForce 256.
GPUs may well have done the same-ish operations for a long time, but they were doing those operations for graphics. GPGPU didn't take off until relatively recently.
It'll be either "cheap" like the DGX Spark (with crap memory bandwidth) or overpriced with the bus width of a M4 Max with the rhetoric of Intel's 50% margin.
Yeah, Intel's problem is that this is (at least) the third time they've announced a new ML accelerator platform, and the first two got shitcanned. At this point I wouldn't even glance at an Intel product in this space until it had been on the market for at least five years and several iterations, to be somewhat sure it isn't going to be killed, and Intel's current leadership inspires no confidence that they'll wait that long for success.
How does LPDDR5 (This Xe3P) compare with GDDR7 (Nvidia's flagships) when it comes to inference performance?
Local inference is an interesting proposition because today in real life, the NV H300 and AMD MI-300 clusters are operated by OpenAI and Anthropic in batching mode, which slows users down as they're forced to wait for enough similar sized queries to arrive. For local inference, no waiting is required - so you could get potentially higher throughput.
I asked GPT to pull real stats on both. Looks like the 50-series RAM is about 3X that of the Xe3P, but it wanted to remind me that this new Intel card is designed for data centers and is much lower power, and that the comparable Nvidia server cards (e.g. H200) have even better RAM than GDDR7, so the difference would be even higher for cloud compute.
Any business people here that can explain why companies announce products a year before their release? I can understand getting consumers excited but it also tells competitors what you are doing giving them time to make changes of their own. What's the advantage here?
In this case there is no risk of anyone stealing Intel's ideas or even reacting to them.
First, they're not even an also-ran in the AI compute space. Nobody is looking to them for roadmap ideas. Intel does not have any credibility, and no customer is going to be going to Nvidia and demanding that they match Intel.
Second, what exactly would the competitors react to? The only concrete technical detail is that the cards will hopefully launch in 2027 and have 160GB of memory.
The cost of doing this is really low, and the value of potentially getting into the pipeline of people looking to buy data center GPUs in 2027 soon enough to matter is high.
Given how long it takes to develop a new GPU I’m pretty sure this one was signed off by Pat and given it survived Lip-Bu’s axe that says something, at least for Intel.
If customers know your product exists before they can buy it then they may wait for it. If they buy the competitor's product today because they don't know your product will exist until the day they can buy it then you lose the sale.
Samples of new products also have to go out to third party developers and reviewers ahead of time so that third party support is ready for launch day and that stuff is going to leak to competitors anyway so there's little point in not making it public.
It can also prevent competitors from entering a particular space. I was told as an undergraduate that UNIX was irrelevant because the upcoming Windows NT would be POSIX compliant. It took a _very_ long time before that happened (and for a very flexible version of "compliant"), but the pointy-headed bosses thought that buying Microsoft was the future. And at first glance the upcoming NT _looked_ as if the TCO would be much lower than AIX, HPuX or Solaris.
Then of course Linux took over everywhere except the desktop.
That wasn't even necessarily false. Windows NT on commodity hardware from the likes of Dell arguably did have a lower TCO than proprietary UNIX on proprietary hardware.
But then Linux on that same commodity hardware was lower yet.
There'll be a good market share for comparatively "lower power/ good enough" local AI. Check out Alez Ziskind's analysis of the B50 Pro [0]. Intel has an entire line-up of cheap GPUs that perform admirably for local use cases.
This guy is building a rack on B580s and the driver update alone has pushed his rig from 30 t/s to 90 t/s. [1]
Yeah even RTX’s are limited in this space due to lack of tensor cores. It’s a race to integrate more cores and faster memory buses. My suspicion is this is more me too product announcement so they can play partner to their business opportunities and continue greasing their wheels.
If you're Intel sized, it's gonna leak. If you announce it first, you get to control the message.
The other thing is enterprise sales is ridiculously slow. If Intel wants corporate customers to buy these things, they've got to announce them ~a year ahead, in order for those customers to buy them next year when they upgrade hardware.
There is a serious possibility this isn’t a bubble. Too many people watched the big short and now call every bull a bubble; maybe the bubble was the dollar and it’s popping now instead.
Have you looked in detail at the economics of this?
Career finance professionals are calling it a bubble, not due to their suddenly found deep technological expertise, but because public cos like FAANG et. al are engaging in typical bubble like behavior: Shifting capex away from their balance sheets into SPACs co-financed by private equity.
This is not a consumer debt bubble, it's gonna be a private market bubble.
But as all bubbles go, someones gonna be left holding the bag with society covering for the fallout.
It'll be a rate hike, it'll be some Fortune X00 enterprises cutting their non-ROI-AI-bleed or it'll be an AI-fanboy like Oracle over-leveraging themselves and then watching their credit default swaps going "Boom!" leading to a financing cut off.
It's possible, circular financing is definitely fishy, but OTOH every openai deal sama makes is swallowed by willing buyers at a fair market price. We'll be in a bubble when all the bears are dead and everyone accepts 'a new paradigm', not before; there's plenty of upside capitulation left judging by some hedge fund returns this year.
...and again, this is assuming AI capability stops growing exponentially in the widest possible sense (today, 50%-task-completion time horizon doubles ~7 months).
AI is not going anywhere. Now everyone wants to get a piece. Local inference is expected to grow. Documents, image, video, etc processing. Another obvious is driverless farm vehicles and other automated equipment. "Assisted" books, images, news,.. already and grows fast. Translation also a fact.
So far there is no 'plateau' in the nearest future. 'AI' as a science and its applications should develop further for the next several years. Models will get more efficient, but still the bigger the better. This is obvious. Even if models don't scale up well, they can be used collectively in parallel 'brainstorming'. This will still create demand for hardware. Stagnation is still possible in case of recession. In this case even stable businesses will suffer.
As for efficiency, replacing one programmer in group of 10 with AI already will increase productivity and lower the price. In most cases. In reality adding AI accounts to existing group works better. This is _now_, not hopes or sci-fi.
That's why I'm saying there is no way back. 'AI winter' is as likely as smartphones winter.
I have no idea of the likely price, but (IMO) this is the sort of disruption that Intel needs to aim at if it's going to make some sort of dent in this market. If they could release this for around the price of a 5090, it would be very interesting.
Maybe not that low, but given it's using LPDDR5 instead of GDDR7, at least the ram should be a lot cheaper.
Certainly an interesting choice. Dramatically worse performance but dramatically larger only time will tell how it actually goes
It‘s LPDDR5X
LPDDR5x really just means LPDDR5 running at higher than the original speed of 6400MT/s. Absent any information about which faster speed they'll be using, this correction doesn't add anything to the discussion. Nobody would expect even Intel to use 6400MT/s for a product that far in the future. Where they'll land on the spectrum from 8533 MT/s to 10700 MT/s is just a matter for speculation at the moment.
With this much ram don’t expect anything remotely affordable by civilians.
160 GB LPDDR5 is ~$1,200 retail so the card could be sold for $2,000. The price will depend on how desperate Intel is. Intel probably can't copy Nvidia's pricing.
Uncle Sam owns a good chunk of Intel now. "Not affordable by civilians" might be precisely the target market: the DoD/national intelligence agencies have money to burn, can fund things long enough to stabilize Intel a little, and in exchange they get first dibs on everything.
Intel for intel on your Intels, perhaps.
I mean, even without that, the phrase “enterprise GPU”, does not tend to convey “priced for typical consumers”.
Xe3P as far as I remember is built in their own fabs as opposed to xe3 at TSMC. This could give them a huge advantage by being possibly the only competitor not competing for the same TSMC wafers
Funny they still call them graphics cards when they're really... I dont know, matmul cards ? Tensor cards ? TPU ? Well that sums it up maybe, what those are are really CUDA cards.
This sounds like a gaming card with extra RAM so it's kind of appropriate to call it a graphics card.
Dude, this is asinine. Graphics cards have been doing matrix and vector operations since they were invented. No one had a problem with calling matrix multiplers graphics cards until it became cool to hate AI.
It was many generations before vector operations were moved onto graphics chips.
I think they’re using “vector” in the linear algebra sense, e.g. multiplying a matrix and a vector produces a different vector.
Not, as I assume you mean, vector graphics like SVG, and renderers like Skia.
If you s/graphics/3d graphics does that still hold true?
Yes. The earliest consumer PC 3D graphics cards just rasterized pre-transformed triangles and that's it; the CPU had to do pretty much all the math (but drawing the pixels was considered the hard part). Later, "Hardware Transform and Lighting (T&L)" was introduced circa 2000 by cards like the GeForce 256.
GPUs may well have done the same-ish operations for a long time, but they were doing those operations for graphics. GPGPU didn't take off until relatively recently.
Between 18A becoming viable and this, it seems Intel is finally climbing out of the hole it's been in for years.
Makes me wonder whether Gelsinger put all this in motion, or if the new CEO lit a fire under everyone. Kinda a shame if it's the former...
Will this have any support for open source libraries like PyTorch or will it be all Intel proprietary software that you need a license for?
Intel puts a huge priority on DL framework support before releasing related hardware, going back to at least 2017.
I assume that hasn't changed.
OpenVino is entirely open-source and can run PyTorch and ONNX models, so this is definitely not a topic of concern. PyTorch also has native Intel GPU support https://docs.pytorch.org/docs/stable/notes/get_start_xpu.htm...
It'll be either "cheap" like the DGX Spark (with crap memory bandwidth) or overpriced with the bus width of a M4 Max with the rhetoric of Intel's 50% margin.
Or it will be cheap, with the ability to expand 8X on a server. Particularly with PCIe 6.0 coming soon, might be a very attractive package.
https://www.linkedin.com/posts/storagereview_storagereview-a...
I remember Larabee and Xeon-Phi announcements and getting so excited at the time. So I'll wait but curb my enthusiasm.
Yeah, Intel's problem is that this is (at least) the third time they've announced a new ML accelerator platform, and the first two got shitcanned. At this point I wouldn't even glance at an Intel product in this space until it had been on the market for at least five years and several iterations, to be somewhat sure it isn't going to be killed, and Intel's current leadership inspires no confidence that they'll wait that long for success.
Xe works much much better than Larabee or Xeon Phi ever did. Xe3 might even be good.
A not-absurdly-priced card that can run big models (even quantized) would sell like crazy. Lots and lots of fast RAM is key.
How does LPDDR5 (This Xe3P) compare with GDDR7 (Nvidia's flagships) when it comes to inference performance?
Local inference is an interesting proposition because today in real life, the NV H300 and AMD MI-300 clusters are operated by OpenAI and Anthropic in batching mode, which slows users down as they're forced to wait for enough similar sized queries to arrive. For local inference, no waiting is required - so you could get potentially higher throughput.
Lpddr5x (not lpddr5) is 10.7 Gbps. Gddr7 is 32 Gbps. So it's going to be slower
Yes but in matrix multiplication there are O(N²) numbers and O(N³) multiplications, so it might be possible that you are bounded by compute speed.
I asked GPT to pull real stats on both. Looks like the 50-series RAM is about 3X that of the Xe3P, but it wanted to remind me that this new Intel card is designed for data centers and is much lower power, and that the comparable Nvidia server cards (e.g. H200) have even better RAM than GDDR7, so the difference would be even higher for cloud compute.
Isn't that precisely what DGX Spark is designed for?
How is this better?
DGX Spark is $4000... this might (might) not be? (and with more memory)
This starts shipping in 2027. I'm sure you can buy a DGX Spark for less than $4k in 2 years time.
But good luck with Nvidia not turning it into abandoware.
Any business people here that can explain why companies announce products a year before their release? I can understand getting consumers excited but it also tells competitors what you are doing giving them time to make changes of their own. What's the advantage here?
In this case there is no risk of anyone stealing Intel's ideas or even reacting to them.
First, they're not even an also-ran in the AI compute space. Nobody is looking to them for roadmap ideas. Intel does not have any credibility, and no customer is going to be going to Nvidia and demanding that they match Intel.
Second, what exactly would the competitors react to? The only concrete technical detail is that the cards will hopefully launch in 2027 and have 160GB of memory.
The cost of doing this is really low, and the value of potentially getting into the pipeline of people looking to buy data center GPUs in 2027 soon enough to matter is high.
Given how long it takes to develop a new GPU I’m pretty sure this one was signed off by Pat and given it survived Lip-Bu’s axe that says something, at least for Intel.
If customers know your product exists before they can buy it then they may wait for it. If they buy the competitor's product today because they don't know your product will exist until the day they can buy it then you lose the sale.
Samples of new products also have to go out to third party developers and reviewers ahead of time so that third party support is ready for launch day and that stuff is going to leak to competitors anyway so there's little point in not making it public.
I don't think you're giving much advantage to anybody really on such a small timeframe.
Semiconductors are like container ships, they are extremely slow and hard to steer, you plan today the products you'll release in 2030.
It can also prevent competitors from entering a particular space. I was told as an undergraduate that UNIX was irrelevant because the upcoming Windows NT would be POSIX compliant. It took a _very_ long time before that happened (and for a very flexible version of "compliant"), but the pointy-headed bosses thought that buying Microsoft was the future. And at first glance the upcoming NT _looked_ as if the TCO would be much lower than AIX, HPuX or Solaris.
Then of course Linux took over everywhere except the desktop.
That wasn't even necessarily false. Windows NT on commodity hardware from the likes of Dell arguably did have a lower TCO than proprietary UNIX on proprietary hardware.
But then Linux on that same commodity hardware was lower yet.
This is a shareholder “me too” product
What are they gonna do with their own FAB?
Not release anything?
There'll be a good market share for comparatively "lower power/ good enough" local AI. Check out Alez Ziskind's analysis of the B50 Pro [0]. Intel has an entire line-up of cheap GPUs that perform admirably for local use cases.
This guy is building a rack on B580s and the driver update alone has pushed his rig from 30 t/s to 90 t/s. [1]
0: https://www.youtube.com/watch?v=KBbJy-jhsAA
1: https://old.reddit.com/r/LocalLLaMA/comments/1o1k5rc/new_int...
Watson…
Yeah even RTX’s are limited in this space due to lack of tensor cores. It’s a race to integrate more cores and faster memory buses. My suspicion is this is more me too product announcement so they can play partner to their business opportunities and continue greasing their wheels.
If you're Intel sized, it's gonna leak. If you announce it first, you get to control the message.
The other thing is enterprise sales is ridiculously slow. If Intel wants corporate customers to buy these things, they've got to announce them ~a year ahead, in order for those customers to buy them next year when they upgrade hardware.
To keep investors happy and stock from failing? Fairy tales work as well, see Tesla robots.
> What's the advantage here?
Stock number go up
The AI bubble might not last another year. Better get a few more pumps in before it blows.
There is a serious possibility this isn’t a bubble. Too many people watched the big short and now call every bull a bubble; maybe the bubble was the dollar and it’s popping now instead.
Have you looked in detail at the economics of this?
Career finance professionals are calling it a bubble, not due to their suddenly found deep technological expertise, but because public cos like FAANG et. al are engaging in typical bubble like behavior: Shifting capex away from their balance sheets into SPACs co-financed by private equity.
This is not a consumer debt bubble, it's gonna be a private market bubble.
But as all bubbles go, someones gonna be left holding the bag with society covering for the fallout.
It'll be a rate hike, it'll be some Fortune X00 enterprises cutting their non-ROI-AI-bleed or it'll be an AI-fanboy like Oracle over-leveraging themselves and then watching their credit default swaps going "Boom!" leading to a financing cut off.
It's possible, circular financing is definitely fishy, but OTOH every openai deal sama makes is swallowed by willing buyers at a fair market price. We'll be in a bubble when all the bears are dead and everyone accepts 'a new paradigm', not before; there's plenty of upside capitulation left judging by some hedge fund returns this year.
...and again, this is assuming AI capability stops growing exponentially in the widest possible sense (today, 50%-task-completion time horizon doubles ~7 months).
AI is not going anywhere. Now everyone wants to get a piece. Local inference is expected to grow. Documents, image, video, etc processing. Another obvious is driverless farm vehicles and other automated equipment. "Assisted" books, images, news,.. already and grows fast. Translation also a fact.
The technology, maybe - and if on local.
The public co valuations of quickly depreciating chip hoarders selling expensive fever dreams to enterprises are gonna pop though.
Spend 3-7 USD for 20 cents in return and 95% project failures rates for quarters on end aren't gonna go unnoticed on Wall St.
So far there is no 'plateau' in the nearest future. 'AI' as a science and its applications should develop further for the next several years. Models will get more efficient, but still the bigger the better. This is obvious. Even if models don't scale up well, they can be used collectively in parallel 'brainstorming'. This will still create demand for hardware. Stagnation is still possible in case of recession. In this case even stable businesses will suffer.
As for efficiency, replacing one programmer in group of 10 with AI already will increase productivity and lower the price. In most cases. In reality adding AI accounts to existing group works better. This is _now_, not hopes or sci-fi.
That's why I'm saying there is no way back. 'AI winter' is as likely as smartphones winter.
Sound as if it won‘t be widely available before 2027 which disappointing for a 341GB/s chip.
Intel leadership actually reads HN? Mindblown...