Intel's Battlemage Architecture

All sources I've seen say the 4060 Ti 8GB is also really bad value. Here’s GamersNexus for example: https://www.youtube.com/watch?v=Y2b0MWGwK_U.

> Intel takes advantage of this by launching the Arc B580 at $250, undercutting both competitors while offering 12 GB of VRAM.

Not sure where you got that 350 EUR number for B580?

Been running Linux on the A770 for about 2 years now. Very happy with the driver situation. Was a bit rough very early on, but it's nice and stable now. Recommend at least Linux 6.4, but preferably newer. I use a rolling release distro(Artix) to get up to date kernels.

ML stuff can be a pain sometimes because support in pytorch and various other libraries is not as prioritised as CUDA. But I've been able to get llama.cpp working via ollama, which has experimental intel gpu support. Worked fine when I tested it, though I haven't actually used it very much, so don't quote me on it.

For image gen, your best bet is to use sdnext(https://github.com/vladmandic/sdnext), which supports Intel on linux officially, and will automagically install the right pytorch version, and do a bunch of trickery to get libraries that insist on CUDA to work in many of the cases. Though some things are still unsupported due to various libraries still not supporting intel on Linux. Some types of quantization are unavailable for instance. But at least if you have the A770, quantisation for image gen is not as important due to plentyful VRAM, unless you're trying to use the flux models.

Yes, first party drivers are made. Upstream Linux and mesa project should have good support in their latest releases. If you're running a non-bleeding edge distro, you may need to wait or do a little leg work to get the newer versions of things, but this is not unusual for new hardware.

If you're running Ubuntu, Intel has some exact steps you can follow: https://dgpu-docs.intel.com/driver/client/overview.html

Intel also have up-streamed their video encoding acceleration support into software like ffmpeg.

Intel Arc gpus also support hardware video encoding for the AV1 codec which even the just released Nvidia 50 series still doesn't support.

Of all the god awful Linux GPU drivers Intel's are the least awful IME. Unless you're talking purely compute, then nvidia, have fun matching those cuda versions though...

I have always associated Intel iGPUs with good drivers but people seem to often complain about their Linux dGPU drivers in these threads. I hope it is just an issue of them trying to break into a new field, rather than a slipping of their GPU drivers in general…

Here are some benchmarks from a few months back. Seems promising. https://www.phoronix.com/review/intel-arc-b580-gpu-compute

Whoops - included the wrong link! https://www.phoronix.com/review/intel-arc-b580-graphics-linu...

I use an Alchemist series A380 on my nix media server, but it's absolutely fantastic for video encoding.

In fact, Intel has been a stellar contributor to the Linux kernel and associated projects, compared to all other vendors. They usually have launch day Linux support provided that you are running a bleeding edge Linux kernel.

The amount of memory you can put on a GPU is mainly constrained by the GPU's memory bus width (which is both expensive and power hungry to expand) and the available GDDR chips (generally require 32bits of the bus per chip). We've been using 16Gbit (2GB) chips for awhile, and they're just starting to roll out 24Gbit (3GB) GDDR7 modules, but they're expensive and in limited demand. You also have to account for VRAM being somewhat power hungry (~1.5-2.5w per module under load).

Once you've filled all the slots your only real option is to do a clamshell setup that will double the VRAM capacity by putting chips on the back of the PCB in the same spot as the ones on the front (for timing reasons the traces all have to be the same length). Clamshell designs then need to figure out how to cool those chips on the back (~1.5-2.5w per module depending on speed and if it's GDDR6/6X/7, meaning you could have up to 40w on the back).

Some basic math puts us at 16 modules for a 512 bit bus (only the 5090, have to go back a decade+ to get the last 512bit bus GPU), 12 with 384bit (4090, 7900xtx), or 8 with 256bit (5080, 4080, 7800xt).

A clamshell 5090 with 2GB modules has a max limit of 64GB, or 96GB with (currently expensive and limited) 3GB modules (you'll be able to buy this at some point as the RTX 6000 Blackwell at stupid prices).

HBM can get you higher amounts, but it's extremely expensive to buy (you're competing against H100s, MI300Xs, etc), supply limited (AI hardware companies are buying all of it and want even more), requires a different memory controller (meaning you'll still have to partially redesign the GPU), and requires expensive packaging to assemble it.

You'd need memory chips with double the memory capacity to slap the extra vram in, at least without altering the memory bus width. And indeed, some third party modded entries like that seem to have shown up: https://www.tomshardware.com/pc-components/gpus/nvidia-gamin...

As far as official products, I think the real reason another commentator mentioned is that they don't want to cannibalize their more powerful card sales. I know I'd be interested in a lower powered card with a lot of vram just to get my foot in the door, that is why I bought a RTX 3060 12GB which is unimpressive for gaming but actually had the second most vram available in that generation. Nvidia seem to have noticed this mistake and later released a crappier 8GB version to replace it.

I think if the market reacted to create a product like this to compete with nvidia they'd pretty quickly release something to fit the need, but as it is they don't have too.

Bandwidth. GDDR / HBM, both used by GPU depending on usage are high bandwidth low capacity, comparatively speaking. Modern GPU tries to put more VRAM with more memory channel up to 512bit but requires more die space and hence are expensive.

We will need a new memory design for both GDDR and HBM. And I wont be surprised they are working on it already. But hardware takes time so it will be few more years down the road.

Because then they couldn't sell you the $10k enterprise GPU

You can actually getting GPUs from the Chinese markets (e.g., AliExpress) that have had their VRAM upgraded. Someone out there is doing aftermarket VRAM upgrades on cards to make them more usable for GPGPU tasks.

Which also answers your question: The manufacturers aren't doing it because they're assholes.

Seems some years away to get that into consumer price range.

Increasing clocks tends to have a greater-than-linear cost on power, as you need transistors to switch quicker so often need a higher voltage, which causes more leakage and other losses on top of the switching cost itself (that all turn into heat). Higher clock targets also have a cost for the design itself, often needing more transistors for things like extra redrivers to ensure you get fast switching speed, or even things like more pipeline stages. Plus not all area is "transistors" - it's often easier to place related units that need a lot of interconnectivity with shorter interconnects if an adjacent, less interconnected unit isn't also trying to be packed into much of the same space, routing on modern chips is really difficult (and a place where companies can really differentiate by investing more).

For tasks that tend to scale well with increased die area, which is often the case for GPUs as they're already focused on massively parallel tasks so laying down more parallel units is a realistic option, running a larger die at lower clocks is often notably more efficient in terms of performance per unit power.

For GPUs generally that's just part of the pricing and cost balance, a larger lower clocked die would be more efficient, but would that really sell for as much as the same die clocked even higher to get peak results?

>I thought (bigger die ^ bigger wires -> more current -> higher consumption).

All things being equal, a bigger die would result in more power consumption, but the factor you're not considering is the voltage/frequency curve. As you increase the frequency, you also need to up the voltage. However, as you increase voltage, there's diminishing returns to how much you can increase the frequency, so you end up massively increasing power consumption to get minor performance gains.

If it's a similar number of transistors on a larger die then I can believe the power consumption is good. Less dense layout probably requires less design effort and may reduce hotspots.

If Intel is getting similar performance from more transistors that could be caused by extra control logic from a 16-wide core instead of 32.

It mainly seems to boil down to design choice and process technology.

They might be targeting a lower power density per squad mm than compared to amd or nvidia, focusing more on lower power levels.

Instruction set architecture and layout of the chips and PCB also factor into this as well.

They are holding back the higher vram models of this card. GPU makers always do some nerfing of their cards in the same product line. Often times there’s no good reason for this other than they found specs that they can market and sell simply by moving voltages around.

Anyway, expecting good earnings throughout the year as they use Battlemage sales to hide the larger concerns about standing up their foundry (great earnings for the initial 12gb cards, and so on for the inevitable 16/24gb cards).

> I thought (bigger die ^ bigger wires -> more current -> higher consumption).

I am not a semi expert but bigger die doesn't mean bigger wires if you are referring to cross-section, the wires would be thinner meaning less current. Power is consumed pushing and pulling electrons from the transistor gates which are all of the FET type, field effect transistor. The gate is a capacitor that needs to be charged to open the gate to allow current to flow through the transistor. discharging the gate closes it. That current draw then gets multiplied by a few billion gates so you can see where the load comes from.

> 4060 performance

That’s really not true though. It’s closer to 4060 Ti and somewhat ahead/behind depending on specific game.

> I am not too impressed with the "chips and cheese ant's view article" as they don't uncover the reason why performance is SO PATHETIC!

Performance on GPU has always been about Drivers. Chip and Cheese is only here to show the uArch behind it. This isn't even new as we should have learned all about it during Voodoo 3Dfx era. And 9 years have passed since an ( now retired ) Intel Engineers said that they would be completing against Nvidia by 2020 if not 2021. We are now in 2025 and they are not even close. But somehow Raja Koduri was suppose to save them and now gone.

The generations are all fantasy type names in alphabetical order. The first was Alchemist (and the cards were things like A310) and the next is Celestial. Actually when I think about product names for GPUs and CPUs these seem above average in clarity and only slightly dorkier than average. I'm sure they'll get more confusing and nonsensical with time as that seems to be a constant of the universe.

It sounds cool and has actual personality. What would you prefer, Intel Vision Pro Max? :)

It's their 2nd generation, the 'B' series. The previous was their 'A' / Alchemist.

> According to Intel, the brand is named after the concept of story arcs found in video games. Each generation of Arc is named after character classes sorted by each letter of the Latin alphabet in ascending order. (https://en.wikipedia.org/wiki/Intel_Arc)

It's dorky but there isn't much else to say about it. Personal GPU enthusiasts are almost always video game enthusiasts so it's not really a particularly weird name in context.

Cool name, easy to remember, aint it?

A codename as good as any. Nvidia has Tesla, Turing etc.

A well-known commercial storage vendor gives their system releases codenames from beer brands. We had Becks, Guinnes, Longboard, Voodoo Ranger, and many others. Presumably what the devs drank during that release cycle, or something ;-)

It's fun for the developers and the end-users alike... So no, it's not limited to GPU enthusiasts at all. Everyone likes codenames :)