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NVIDIA is one of the most open labs. They even share many of their pre-training and even post-training datasets for Nemotron on HuggingFace; for example: https
by dannyw 2mo ago
NVIDIA is one of the most open labs.
They even share many of their pre-training and even post-training datasets for Nemotron on HuggingFace; for example: https://huggingface.co/datasets/nvidia/Nemotron-Post-Training-Dataset-v2 https://huggingface.co/datasets/nvidia/Nemotron-Post-Trainin...
Which other lab shares this?
Yes, there is no question NVIDIA wants to lock you into CUDA and their hardware. But also, they’ve consistently demonstrated the most openness when it comes to model training, datasets, and research; even before the LLM era (e.g. StyleGAN).
There’s also modelscope.cn (china’s huggingface) which is worth checking out. I would not be surprised if one day, we have to use China VPNs to download open weight models.
- jrflowers 2mo agolol “Everything you said is correct but you’re wrong because I’m thinking about something other than what you were talking about”
- bigyabai 2mo agoCUDA is proprietary for a pretty understandable reason. There's no good way for Nvidia to standardize it. They supported OpenCL when Khronos floated the idea of a GPGPU standard to manufacturers, but OEMs didn't want to design scalable hardware or sponsor the software.
- willy_k 2mo agoNVIDIA is a lot more than a “lab”.
- matheusmoreira 2mo ago> NVIDIA is one of the most open labs. Of course they are. They're commoditizing their complement. I want to own the hardware, not play around in an nvidia fiefdom full of nvidia rules.
- bdangubic 2mo agonothing stopping you from doing that
- Forgeties79 2mo agoAre you joking? They just bought HF for $13bill and didn’t break a sweat. They are dominant and spreading.
- behringer 2mo agoCan't buy a decent modern Intel gpu to run AI on because of nividias "donation"
- vee-kay 2mo ago[dead]
- high_na_euv 1mo agoBut Crescent Island is expected to appear soon
- dannyw 1mo agoThe Intel Arc Pro B60 Dual has 48GB of VRAM; and the B70 goes up to 32GB.
- mstkllah 1mo agoWhat is the support like for them? Can they be seriously considered as alternatives to Nvidia or AMD cards? I have been looking into buying a GPU, specifically the Radeon R9700 AI Pro but noticed the Intel cards too and was not sure what you make of them.
- behringer 1mo agoI stand corrected. For some reason I had written off this generation but it does look capable.
- bigyabai 2mo agoYou do own the hardware. Nvidia GPUs have FOSS driver alternatives (Nouveau, NOVA) and have supported OpenCL on the proprietary drivers since 2009. If you don't want to use CUDA, they expose the PTX bindings to write your own CUDA alternative too: https://docs.nvidia.com/cuda/parallel-thread-execution/index.html https://docs.nvidia.com/cuda/parallel-thread-execution/index...
- bayindirh 2mo agoWhen last looked at it, NVIDIA was not supporting OpenCL beyond 1.0. Also, when running OpenCL, NVIDIA hardware disables multiple DMA engines, and allows only one memory transfer at a time to prevent OpenCL running as fast as CUDA. Did NVIDIA finally allow open source drivers to access all parts and features of the card to allow feature parity? Last time I checked they were considering a plan for planning a solution to that.
- pjmlp 2mo agoPeople love to blame NVidia on OpenCL failure, maybe Intel and AMD should actually deliver something compute researchers want to use?
- bayindirh 1mo agoI love your insights which enlighten my blind spots most of the time, but I didn't blame NVIDIA for OpenCL's failure. I just noted a company's choices when it comes to a competing set of libraries w.r.t. to their native ones. Having said that, I'll try compiling a OpenCL 3.0 program in the cluster, so I can report whether NVIDIA runs this software, and if yes, how well.
- pjmlp 1mo agoYeah, however if Intel and AMD actually delivered a working 2.0 with proper support for C++ and Fortran, maybe the OpenCL 3.0 back to 1.0 reboot would not have been needed. Likewise SYSCL although built on top of OpenCL 3.0 primitives, is mostly Intel, which also owns CodePlay, the company that delivered the first working SYSCL compute experience, again neither AMD nor Intel (until it bought CodePlay).
- deleted 2mo ago[deleted]
- wjnc 2mo agoI'll expand on the economics somewhat. My intuition is that you can like a moat left of you in the supply chain, but dislike moats to the right of you. (I'm using left and right as I picture this horizontally drawn. It is usually called vertical integration by economists.) But free competition in your market is worst of all. Free competition right outside your moat is pretty sweet, and that's were parent is commenting on. Nvidia probably likes that ASML is a monopolist (it's called a monopsony). The price is high and Nvidia can't scale as hard as they want to (more general: capital intensive market). This monopsony makes sure that other chip companies can't rapidly scale up and try to beat Nvidia. That there only ever was one other GPU firm (I'm prehistoric; once there were more) and they bungled it on software, is pretty sweet for Nvidia. On the side of their customers. It would be best for Nvidia if there is free competition for the outputs generated from there GPUs. This maximizes consumer surplus and thus demand. Maximum demand for tokens, is maximal demand feeded in their monopoly. If there is a monopoly right from you, demand is curtailed, and your value is limited. And that exactly is why you see interest from token generators for chips. Bridge that moat and gain a larger value surplus. Both NVidia and, say, China actively undercutting the token-supplier value chain is quite interesting to watch. It's like the Opium wars with us as somewhat happy customers. In this same vein, why isn't ASML raising thousands of billions for building their own (subsidiary) chip foundries, while raising prices and starving the market (a little) for their machines.
- patrickk 1mo ago> In this same vein, why isn't ASML raising thousands of billions for building their own (subsidiary) chip foundries, while raising prices and starving the market (a little) for their machines. You're looking this purely through an economic lens, while in reality geopolitical factors play a huge role in what ASML can and cannot do. The US government would likely take an extremely dim view of any new external competitor popping up for their chip foundry industry (especially with all the new US plants being built or planned) and would lean heavily on their vassal/ally the Netherlands to prevent this. Unlike with China, the US has more leverage over the Netherlands[1] The US security state and US tech giants are joined at the hip, as they have been since the beginning of Silicon Valley[1], right through the Snowden revelations through to the present day[2]. [1] https://nltimes.nl/2026/08/20/us-preparing-force-netherlands-ban-asml-selling-china https://nltimes.nl/2026/08/20/us-preparing-force-netherlands... [2] https://www.brennancenter.org/our-work/research-reports/section-702-foreign-intelligence-surveillance-act-fisa-2026-resource-page https://www.brennancenter.org/our-work/research-reports/sect...
- Iolaum 2mo agoWhile nvidia 's drivers are closed source there's enough interest in running LLM's that you are not locked in using nvidia. Strix Halo chips have been around before dgx spark came out and deliver very similar performance.
- amelius 2mo ago> > NVIDIA is one of the most open labs. > Of course they are. They're commoditizing their complement Then why don't they sell consumer GPUs with tons of memory. They clearly segment the market into consumer versus server/business.
- HanClinto 1mo agoThe upcoming RTX Spark [0] is aiming to fill that space -- consumer GPUs with tons of memory. [0] - https://www.nvidia.com/en-us/products/rtx-spark/ https://www.nvidia.com/en-us/products/rtx-spark/
- SuchAnonMuchWow 1mo agoThis is not a GPU, this is a laptop SoC with CPU and integrated GPU, and knowing nvidia it will probably be even more closed than an intel CPU. You will own even less of your hardware
- deleted 1mo ago[deleted]
- bigyabai 1mo agoNearly all ARM CPUs are "even more closed than an intel CPU" on a driver level. Nvidia stands out by supporting UEFI on ARM, which even Apple refuses: https://docs.nvidia.com/dgx/dgx-spark/uefi-settings.html https://docs.nvidia.com/dgx/dgx-spark/uefi-settings.html
- pizza234 1mo agoThere are - see the RTX Pro 6000, which has 96 GB. There are a few problems though, primarily, a GPU with lots of VRAM and very high bandwidth is inherently very expensive (on top of which there is also the CUDA premium); AI use cases are better served by SoCs with lower (but still high) bandwidth and more RAM.
- tannertech 2mo agoI'm with Torvalds here, fuck you Nvidia.
- user_7832 2mo ago"The proprietary shovel seller has some excellent tutorials on how to dig gold. Nobody else has such good step by step guides. Therefore them buying a shovel-agnostic tutorials and techniques method (that has a lot of info on using other shovels effectively) is justified."
- csomar 2mo agoThey are sharing stuff that makes you consume their stuff. Their position with big ai companies is always vulnerable (asics/direct tsmc relations)
- raincole 2mo ago> They are sharing stuff that makes you consume their stuff No shit Sherlock. Name one company that shared their code to make you NOT to consume their stuff?
- teiferer 1mo agoWell if you find that obvious (I also do) then why do you not find their motives in acquiring HF onvious or that this move would be bad for the ecosystem as a whole? Cause it's all kinda the same thing.
- jgilias 2mo ago_why_ have people started to call companies “labs”?!
- reverius42 2mo agoBecause making new AI models is a research activity, so the group within Nvidia (or other companies) that does that activity is called a research lab, or just "lab" for short. I don't think anyone is saying that all of Nvidia is a lab (that's just shorthand I guess).
- hnlmorg 1mo agoWhat amuses me is that “lab” is shorthand for “laboratory” and virtually no computer research happens inside a room people would typically call a lab. It’s a little like the trend of calling developers “engineers”. There’s no actual engineering in the traditional sense but I’m sure developers think it sounds cool to call themselves that.
- alex-robbins 1mo agoIf you can't tell the difference between computer science and software engineering, then at least one of those worlds contains none of your feet.
- hnlmorg 1mo agoThat’s not what I said and the snarky remark about my experience is unwarranted (I have more experience in “software engineering” than many on here have been alive) My point was just that I just find it amusing that people call themselves engineers when the code they produce is so far removed from the level of rigour one would expect in literally any other engineering industry. I say this as someone who also has family and friends who are actual engineers, if they built bridges and buildings to the same standards that many developers write code, then people would die. This isn’t meant as a criticism of developers, by the way. Just an observation at the vast differences in the domains and thus the tolerance for errors in the process. Likewise for labs. I’ve worked in AI startups and the science departments are not something one would think of when you say “laboratory”. I get why the term is used, but it’s still amusing. I know language isn’t static. It’s something that evolves, like how a “computer” used to refer to a person rather than a thing, but that doesn’t stop me from being amused. But maybe the real issue here is I take myself less seriously than others so I have that capacity to be amused by the titles I’ve held?
- lsofzz 2mo ago> NVIDIA is one of the most open labs. Dude, where's the src for GPU drivers and the firmware blobs? Sorry, you can't say it is one of the most open labs without qualifying a proper response to the question above.
- girvo 2mo ago"Labs" here specifically means "AI/LLM model lab", which that part of Nvidia is unquestionably one of the most open. Nvidia is also one of the most closed hardware developers around. Two things can be true.
- xg15 2mo agoThen this whole comment thread was a diversion though, as it was specifically about the hardware parts and not model training.
- girvo 1mo agoWell, the entire context is Nvidia acquiring HF, which is very much in the "lab" side of things, so it's in my opinion slightly blurrier than that. But it is a good example of people talking past one another and not communicating well, I would think.
- dragandj 1mo ago/s I thought AI can now give us the source of any binary? What happened to all the vibe coded Nvidia/CUDA drivers?
- pyrale 2mo ago> NVIDIA is one of the most open labs. Nvidia’s history with linux shows the opposite. And as a user running models on a linux/AMD stack, this information does not fill me with hope.
- teiferer 1mo ago"lab" vs "company as a whole" They might be right w.r.t. openness about LLM at the moment, but w.r.t. general software openness they are definitely the opposite of open.
- lrvick 2mo agoNvidia has closed drivers, which makes them light years behind AMD in trust. Also if we were just discussing labs, Ai2 opens ~everything with dramatically less resources than Nvidia.
- cubefox 2mo agoTheir (not especially great, compared to Chinese ones) models being open weight doesn't even come close to outweigh the effect of CUDA & Co being proprietary and closed.
- sdsuper 2mo agoNot really just to counter Anthropic
- mr_toad 1mo ago> NVIDIA is one of the most open labs. Sure, the models are open weight, but porting the code needed to run them on non-Nvidia hardware is not trivial.
- somebodythere 1mo agoNot with the help of the models!
- amlib 1mo ago> NVIDIA is one of the most open labs. A few years ago everyone said _Open_AI is the the most open labs. How did that turn out? Lots of coy, deceiving actions till the whole company was turned into whatever rent seeking amoral borg adjacent shell of it's former past it is now.