I'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.

> > 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.

While 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.

You 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...

nothing stopping you from doing that

"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.

Because they are mostly research departments (aka a lab) turned into a corp structure. It’s not a new phenomenon, just that until recently labs didn’t get $1T valuations so you see it more now

Because 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).

Because it sounds cool/sciency.

Just like everything AI is a "model". It's actually not, but it sounds cool/sciency.

> 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?

"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.

/s I thought AI can now give us the source of any binary? What happened to all the vibe coded Nvidia/CUDA drivers?

CUDA 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.

He's always been pragmatic - it's just that Nvidia's behavior has AFAICT actually changed.

My pick:

1. Oracle

2. A16Z

3. GameStop

Many open weight models do actually have open training data and training algorithms -- I think especially some from Nvidia!

Dude, many of them are open source and open data on Hugging face, including some Nvidia LLM models.

Totally not sure why any one would use it for anything other then if they stumbled across it and where completely green.

We can stop with these weak excuses since AMD and Intel have done more for open source than Nvidia has, including their GPU drivers for Linux.

Nvidia on the other hand has not and the best they have done is a bunch of closed-source blobs which they do more closed source releases than the rest.

Mojo is open source and targets all GPU architectures for their compiler regardless of the vendor and nvcc targets their own (and both that and CUDA are closed source).

So this is directly an apples to apples comparison.

If you don't own the customer relationship, you don't own the profit. See App store, FB.

NVidia is delivering commodity hardware to the hyperscalers, and would eventually get commodity margins (when hyperscalers make their models work on their own hardware).

Amazing article on relevant economics of squeezing vendors - actually about antitrust ad-models but:

  The answer is that [advertising based] companies are an ideal test case for an increasingly common business meta-model, where companies try to create a consumer surplus at one end in order to maximize their negotiating leverage for capturing the producer surplus everywhere else in their supply chain.

Perhaps not relevant to huggingface, sorry.

It's a clever move if that's what they're doing. They're restricted in China, and are likely to face stiff competition from Chinese chipmakers in the coming years. Acquiring the largest repository of trainable models and ensuring they run better on Nvidia hardware is probably one of the few moves they have for keeping ahead of the competition. I mean, it would be terrible for the consumer, but it does make me think that NVDA is a decent investment.

Just say you don't know.

Mojo was partially open source before Qualcomm bought them, and they were going to do open source it anyway.

Was NVCC or CUDA ever open source since the lifetime of its development?

"That's not how citations work." (Dude on the interwebz, 2026)

But more seriously, this is my first time seeing that as well, and I'm not sure I like it. Citing an LLM is a little like citing Wikipedia to me, you cite the primary source the LLM is quoting directly, not the secondary source.

Even worse is that Gemini's knowledge cutoff is still Jan '25.

2026 equivalent of “my Mama told me”

It came to me in a dream.

We are so used to these numbers being thrown around in the AI era that something one needs a reminder that this is 13 billion, not million. Insane exit by HF.

No company is going to be acquired for their software alone with multi-billion valuations ever again. It should be clear by now that code alone is not where the value is anymore, if it ever was.

Yeah, the price is weird as fuck.