Sadly, as you can tell, they have not taken me up on my requests. Awesome that other people got it working!
What exactly do you feel macOS is missing?
Presumably with the right entitlements you can just hit the same (presumably IOKit) syscalls that driverkit does. But that's an extra layer of reverse engineering, and you're not really using driverkit anymore.
i don't think the issues with the project really are specific to driverkit.
> I have been bothering the VM team for years for VM GPU pass through.
Good luck. I'm sure they're keen on giving people access to this so that people can spend their money on NVIDIA GPUs instead of buying more expensive Macs. :)
Would of course be awesome, but I'd be very surprised if it happened.
(Meanwhile, I'm recompiling Wine to see if I can patch it to address an issue that was hotfixed in Proton two weeks ago but isn't in a CrossOver build yet, so yeah, there's maybe some arguments to be made here that I'd be a potential beneficiary. If I weren't too cheap to spring for an eGPU in today's market, anyway.)
The VFIO-style driver made by the author of this also appears generic enough to support all kinds of PCIe, not just GPUs. Apple might find a way to weasel out of this ("hey, this is for hardware companies and you don't seem to be affiliated with one", "your driver requests too broad access", etc.) if there really is a conflict of interest, but so far, there's a chance it will just get rubber-stamped.
I can see them rejecting it for legitimate reasons, though, at least as far as "legitimate" with Apple goes. This driver is essentially a thin layer over PCIDriverKit, exposing all functionality that's supposed to be behind the entitlement to arbitrary applications, in similar fashion to WinRing0. They probably didn't come up with all this bureaucracy only to sign something like that in the end. We'll see what happens.
[0] https://github.com/scottjg/qemu-vfio-apple/blob/84ecdcf5db6b...
[1] https://developer.apple.com/documentation/pcidriverkit/creat...
1. Virtualization.framework seems to support some form of GPU passthrough from the host (granted, not eGPU - it's for the integrated GPU). I think the primary use case is having macOS guests get acceleration, while still sharing GPU time with the host. There is also a patch that recently hit QEMU mainline that supports using the "venus server" with virtio-gpu to support a similar functionality for Linux guests under Hypervisor.framework.
2. Apple internally has some kind of PCI Passthrough support available in Virtualization.framework. It seems like the code is shipped to customers in the framework, but it relies on some kind of kext or kernel component that isn't shipped in retail macOS. I can't say if that's intended to ever be released to customers, but clearly someone at Apple has thought about this the feature.
Unless there's another method I missed, the internal GPU "pass through" of Virtualization.framework you're thinking of might actually just be paravirualization, at least that's what the name suggests. It's implemented in the public ParavirtualizedGraphics framework [0], albeit for PG on Arm macOS, the relevant interfaces are private [1]. I haven't looked that deep into it per se, but, fixing the bugs around it, I've run into a few clues suggesting that it's just a command stream + shared memory being passed around. It also uses its own generic driver on the guest side.
Great job, by the way! Love how authors of pieces like this casually come here to comment :)
[0] https://developer.apple.com/documentation/paravirtualizedgra...
[1] https://github.com/qemu/qemu/blob/edcc429e9e41a8e0e415dcdab6...
There's some randomness around Tahoe for FileVault and it crashing because Data is detected as not encrypted (and that's not OK on bare metal). If hitting that case you might need to enable FileVault inside the VM (and remember to sync aux storage afterwards if not done)
there also appears to be a generic pci passthrough path. we were discussing it on the qemu-devel list: https://lore.kernel.org/qemu-devel/C35B5E97-73F2-4A60-951B-B...
Will Apple ever make a computer that makes Siracusa happy? (and do you have the "Believe" shirt?)
Now they gave up on the workstation market that really enjoys their slots for all myriad of cards.
Having a thunderbolt cable salad is only for those that miss external extensions from 8 and 16 bit home computer days.
Which is clearly what Apple is nowadays focused, if you look back at the vertical integrations before the PC clones market took off.
So now if you really need a workstation, it is either Windows, or one of those systems sold with Red-Hat Enterprise/Ubuntu from IBM, Dell , HP.
I haven’t seen a non-laughable workstation config from the big vendors since the dot com bubble. Presumably they exist, I guess?
It is too inefficient to design a machine which _might_ have two GPU and a flock of additional drives installed into it. It just makes sense to instead design around having independent hardware in its own case, which can meet its own power/cooling needs. This has been a design goal since the trashcan Mac.
Having a PCIe bus increases bandwidth and reduces latency, but once you account for eGPU and for people who would be happy building custom solutions on platforms other than macOS, there's likely not enough identified market for a modular design.
Even if the drivers loaded, they can't talk to the GPU from within docker (unless one implements PCI passthrough). MacOS owns the PCI bus in this scenario.
Anyway, the Mac Pro is dead now. There's only so much sales audio and video professionals can provide.
https://www.reddit.com/r/hardware/comments/1hmgmuf/apples_hi...
Arguably more petty. SJ has been dead for almost 15 year now, I imagine the C-suite might get over it at some point.
Things have moved on since the days where GPUs in Macs were a priority.
But then the AI race has changed things. So who knows - maybe we will one day see official eGPU support from Apple and new drivers from nVidia. Wouldn't put on money on it though....
I don’t know about that. Apple supported some full size GPUs in past product lines and the number of users was very small. Granted, LLMs change that demand but the audience for Mac Pro buyers who would use a full-size GPU that is impossible to obtain is almost nothing compared to their laptop sales.
Part of the reason the new Mac Pro failed to find an audience can definitely be blamed on macOS' hostility to third party hardware. Who knows what Apple would be worth if they beat Nvidia's Grace CPU to the datacenter market. It was certainly their opportunity.
It isn't only audio and video.
The game benchmarks are fun but the LLM improvements are where this gets really interesting for practical use. I love Apple platforms as an approachable way to run local models with a lot of RAM, but their relatively slow prompt processing speed is often overlooked.
> Here you can see the big issue with Macs: the prompt processing (aka “prefill”) speed. It just gets worse and worse, the longer the prompt gets. At a 4K-token prompt, which doesn’t seem very long, it takes 17 seconds for the M4 MacBook Air to parse before we even start generating a response. Meanwhile, if you strap the eGPU to it, it’ll only take 150ms. It’s 120x faster.
The prefill problem goes unnoticed when you’re playing around with the LLM with small chats. When you start trying to use it for bigger work pieces the compute limit becomes a bottleneck.
The time to first token (TTFT) charts don’t look bad until you notice that they had to be shown on a logarithmic scale because the Mac platforms were so much slower than full GPU compute.
EDIT: since Aurornis beat me by 3 minutes, I’ll add another interesting tidbit instead :)
NVIDIA tensor cores on consumer GPUs are massively less powerful per SM core than on their datacenter counterparts-parts (which also makes them easier to get to peak efficiency on consumer GPUs because the rest of the pipeline is much more quickly a bottleneck as per Amdahl’s Law).
This is potentially changing with Vera Rubin CPX which looks an awful lot like a RTX 5090 replacement but with the full-blown datacenter tensor cores (that won’t be available unless you pay for the datacenter SKU) - so it will have very high TFLOPS relative to its bandwidth.
The target market for the CPX is exactly this: prefill and Time To First Token. You can basically just throw compute at the problem for (parts of) prefill performance (but it won’t help anything else past a certain point) and the 5090/M5 are nowhere near that limit.
So the design choice for NVIDIA/Apple/etc of how much silicon to spend for this on consumer GPUs is mostly dictated by economics and how much they can reuse the same chips for the different markets.
The RTX 5090 has an incredible amount of compute performance for matrix operations and a lot of memory bandwidth. The Apple Silicon parts have unusually high memory bandwidth for general purpose compute chips, which is why they can generate tokens so fast. Their raw matrix compute performance is amazing for their power envelope but not nearly as fast as a dedicated GPU consuming 400-500W.
Apple added tensor cores on the M5 generation which help with those matrix operations, which is why the M5 performs so much better than the M4 Max in that article.
Dedicate GPUs like the RTX 5090 are in another league, though.
You can see the divergence in the high resolution gaming benchmarks, too. Once he starts benchmarking at 4K or 6K where the CPU emulation stops being a bottleneck, the raw compute of the 5090 completely crushes any of the Apple Silicon GPUs.
because the GPUs aren't as fantastic as everyone assumes?
> might also be less optimised in MLX?
prefill has gotta be one of the most optimized paths in MLX...
Seeing the author present their results like this give off the impression that they’re biased, which I am sure they aren’t.
I understand that this is true it seems that Doom does support Vulkan but you would need to add VK_NV_glsl_shader to MoltenVK. Probably much less work than what went into hanging an RTX 5090 off of a M4. Still, kudos to the scott and the local AI Inference speeds are pretty cool. What a crazy project! <applause>
(EDIT: Apple agrees with my impression. “To use an eGPU, a Mac with an Intel processor is required.” And, on top of that, the officially supported eGPUs were all AMD not NVIDIA. https://support.apple.com/en-us/102363)
It'd be amazing if Apple would provide better support, and allow more than that 1.5 GB window to make this easier. Arm overall has some quirks with PCIe devices, but at least in Linux, it's gotten so much easier since most modern drivers treat arm64 as a first class citizen.
this is only speculation, but i think the big thing that makes tinygrad slow is that the tinygrad inference engine has not really been optimized much for all these open LLM models. probably most of the work has gone towards optimizing the stack for george's self-driving hardware company. since you can't just run the existing CUDA kernels on their engine, that makes things a lot tougher, engineering-wise.
i am actually curious if my project could share a macos host driver with them. i think it would need some changes, but it seems like there's a lot of overlap
The problem is `max-num-seqs` and `max-model-len` fight each other, and unless you're in the pure single-client mode you'll need multiple slots so to speak.
Hopefully in 2026 the Valve Index VR headset which is ARM (Qualcomm?) we get what you're talking about here - basically proton for Win32/64 to Linux ARM64.
Side note that Windows on ARM isn't bad just that its priced out of its league and cooling is awful for gaming on current laptops. The only issue I had was OpenGL needing some obscure GL on DirectX thing for Maya3D to get games to work.
But Valve's ARM efforts even mean that Android devices can play some (mostly less graphically intensive) Steam games. That makes me very excited about the prospects for the future of gaming handhelds.
Or, more likely, it will tell you something it doesn't know.
Reminds me of yesterday, when I was arguing with ChatGPT that the 5070TI was an actual video card. It kept trying to correct me by saying I must have meant a 4070ti, since no such 5070ti card exists.
I asked Claude to generate an HTML page about PowerShell 7. It gave me a page saying 7.4 was the latest LTS release. I corrected it with links showing 7.6 was released in March and asked it to regenerate with the latest information.
It generated basically the same page with the same claim that 7.4 was the latest release.
People do this too though. At least the AI generally tries to follow instructions that you give it even when you are lacking clarity in the details.
I feel like it's similar to the self-driving car problem. The car could have 99.9999% reliability, drive much better and safer than a human, yet folks will still freak out about a single mistake that's made even though you have actual humans today driving the wrong way down the highway, crashing in to buildings, drunk driving, stealing cars, and all sorts of other just absolutely stupid things.
We need to move away from this idea that because it's an AI system it should give you perfect responses. It's not a deterministic system and it can be wrong, though it should get better over time. Your Google search results are wrong all the time too. The NYT writes things that are factually incorrect. Why do we have such a high standard for these models when we don't apply them elsewhere?
"Very deep", "border-line impractical" "in a research-sense" is the perfect summary of this article itself! :)
> Important: Codex CLI no longer exists
> OpenAI discontinued the Codex model + CLI a while back. There is no official binary named codex in any current OpenAI npm packages. OpenAI’s current CLI tool is:
npm install -g openai
The world knowledge of these models is not necessarily up to date :)
edit: I replayed the same prompt into current ChatGPT and it is less clueless now. Maybe OpenAI noticed that it was utterly dumb that GPT-5.whatever didn't believe that Codex existed and fine-tuned it.
I got Fallout 3 working on my M2 MBP as well as it did on Windows back in the day. Temps were cool, battery was decent. If they sold my college years gaming collection (15-ish years ago) in a way that ran natively through GoG or Steam, I'd buy every single title.
Not to mention that Mac owners are a minority share of the PC gaming market. Linux has the right idea, if you don't translate the games then you'll never have true preservation.
They had literally 15 years of warning about this.
I'm not going to blame the developers here because it's not their fault.
The real question is what happens when they drop Rosetta. They promised they'll keep the APIs related to running 32 bit games but can we trust them?
[1] Not at 8k 240 fps of course.
Most people don't need that, but most people don't need an eGPU either. The number of gamers who would switch to Macbook+eGPU is negligible. It's just not compelling. For LLMs, hanging a 5090 off the thunderbolt port makes prompt processing fast, but I will be surprised if the M6 doesn't come with silicon just for that, as its the current gap. M5 is quite adequate for token generation for the price, given the RAM quantity and bandwidth. An M6 that accelerates TTFT would make an eGPU irrelevant.
For gaming, the threadripper gets at least +20FPS for windows vs linux, and some games just freeze for periods of time on linux with things like dynamic frame generation. I have an SSD for windows just for gaming.
Bingo. This is exactly how I use LLM. I like getting a gut check, seeing what the first recommendations are or if there is some deep flaw in what I think the approach is, and I almost never copy/paste whatever it spits back or just follow its instructions.
Another part of me is almost annoyed that Apple's complete apathy toward obvious computing use cases like this is rewarded by a project like this. I feel like Macs and macOS should not be rewarded for being so difficult to extend and use outside of Apple's narrow vision of the use case of their hardware.
Apple used to support this use case wholeheartedly, but we can see that it's abandoned on their end: Intel-only, and the newest generation of AMD GPUs supported are the 6000 series: https://support.apple.com/en-us/102363
I got tired of rewarding Apple for refusing to make a computer that makes the most of the technology available. This stuff is all a lot worse than just moving over to Linux or even Windows. With hardware like the Framework 13 Pro coming out, along with a surprisingly good set of premium PC laptops, I really don't think the Mac hardware is worth it anymore. Others have legitimately caught up, especially with Apple's aging MacBook Pro chassis with the horrible notch.
Of course the author probably did that as a joke.
It’s these people, not the ones who refuse to use LLMs, who are as they say, “cooked”.
"no - not in any practical sense today, and "maybe" only in a very deep, borderline-impractical research sense."
This is why humans will always rule over crappy LLMs.
Or if you're referring to how the OP still decided to go ahead, I've seen AIs go ahead on impractical courses of action many times, and surprisingly succeed on some of them.
Congrats! Each one got what they wanted :).
Unfortunately, I also believe that market forces may push away from this direction, as LLM companies try to capture the value stream
Never let an AI tell you that you cannot do something practical for your own self for research, discovery or for fun.
The only thing that is close to impractical is expecting your non-technical friends or others to follow you without any incentive or benefit.