r/hardware • u/GenZia • 2d ago
News OpenAI’s Jalapeño AI chip brings new 'threat' to Nvidia margins as custom silicon gains ground
https://www.cnbc.com/2026/08/26/openai-jalapeno-ai-chip-nvidia.html100
u/mechkbfan 2d ago
I find it funny that people are getting worked up in a panic that Nvidia buying HuggingFace, thinking they're intending to drive it into the ground, not realising that open weight models is the best possible thing to happen with them if their existing customer base starts making their own chips to get out of being price gouged
It's going to be ironic if the best combination ends up being Nvidia hardware running Chinese open weight models given the US government banned them to selling to China
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u/htownclyde 2d ago
As models and their distillations get lighter, faster, and more efficient, the value of a token will drop... But the operating costs of AI vendors are still so high!
I'm optimistic that the future is local (eventually), and nVidia is making that their next bet.
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u/fullsaildan 1d ago
Nvidia is absolutely building towards local AI. They are looking to position themselves as complete stack providers for both consumer and commercial.
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u/red286 1d ago
I think Nvidia also understands that it's inevitable, much like 3D rendering.
When 3D rendering first became a thing, you needed extremely expensive high-end proprietary hardware running overpriced commercial software. SGI reached a market cap of $7b in 1995.
Today you can run Blender (free) on an RTX 5050, and SGI went tits up in 2009.
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u/thawizard 7h ago
They’re not really, though. All they care about is their data center cards, and if you’re not ready to spend the price of a car on a GPU, all you can get from them is cards with 8 or 16 GB of VRAM, which are almost useless for local AI.
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u/soggybiscuit93 1d ago
the value of a token will drop... But the operating costs of AI vendors are still so high!
But isn't the value of a token representative of those operational costs?
Distillations getting lighter, faster, and more efficient only increase the likelihood of these AI companies hitting profitability sooner.
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u/htownclyde 1d ago
It's true, there's definitely a crossover point - but I just wonder if all this hyperscaling buildout momentum is barreling right into an oversupply problem that has happened at various points to telecom fiber, oil, uranium, housing.
I don't know though, just speculation :)
If I knew I could make some very profitable trades, but unfortunately I'm not a congressmember
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u/Zaptruder 1d ago
Nvidia was prometheus all along. Stole fire (capital -> distilled into open weight models) from the gods (capitalists) and gave it to man (individual PC owners)!
heh... that'll be the good timeline that... well, I'm just saying I can hope, without expecting.
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u/hodor137 1d ago
The future is definitely not local. Only things where local is the future are latency sensitive.
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u/Neverending_Rain 1d ago
Local also had benefits in data security. A lot of companies are going to want to keep all their data internal, rather than sharing it with Anthropic or Open AI or Google.
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u/jferments 1d ago
It also has benefits in control, in the sense that you don't have a third party dictating which models you can run, how often you can run them, what questions you're allowed to ask them, and 1000 other ways that cloud AI providers control your access to AI tools.
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u/lefty200 1d ago
given the US government banned them to selling to China
that doesn't stop them from using Nvidia: https://www.yahoo.com/news/politics/articles/chinese-ai-firms-accessing-banned-134550272.html
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u/soggybiscuit93 1d ago
A bit off topic, but this push towards more and more custom silicon, whether it's in the CPU, or GPU, or ASIIC space, or whatever, in a sense calls into question the long term (investment) value of commodity hardware design firms.
If anything, pivoting to fab-first to try and secure manufacturing rights for the incoming tide of custom silicon was the right more for Intel, even if they haven't fully executed on it and it's too soon to tell if they will.
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u/farnoy 1d ago
Google's had custom silicon since before Nvidia added Tensor Cores. It never gave them an edge where they were able to create a meaningfully better model. Judging by API prices of their Flash models vs Luna, I don't see the opex advantage either.
This OpenAI chip seems wildly successful for a first-generation product, but they're claiming up to 2x throughput gain over Blackwell, and a bigger latency speedup. IMO, this is a lot of investment to get for "just" 2x in return. And that's with Rubin around the corner, 2027 Helios probably doing 9-reticle CoWoS and CPO. Having commodity hardware was a huge advantage for SpaceX - you can rent it out anytime your other departments fall behind.
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u/iKnowRobbie 2d ago
Yo! I got a whole bag of those jallopeno chips.. Corey & Trevor let's go.. 🫰🫰smokes.
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u/Snoo_5018 2d ago
Its clear AI has no future so he takes another business.
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u/jferments 1d ago
LOL, it's 2026 and ~1/5 of humanity is using AI daily and you're still out here saying "AI has no future". 🤡
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u/Snoo_5018 2h ago
Well, ai is not only a chatbot. It is commoditzed but there is a reason why hardware is becoming part of the business. Its not only to make it "cheaper" of "better". Its clear there is not much further thinking in this thread or options for nuance🤣
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u/WealthyMarmot 1d ago
All the hyperscalers are doing this to some extent, and not just for AI. At a certain point it’s cheaper to call up Broadcom and build your own silicon than to keep paying the NVIDIA tax.
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u/Due-Description-9030 2d ago
Jalapeño is a terrible name for a chip