MangoCoffee

its hyperscalers and neoclouds data center build out that ate those trillions.

a lot of those money is the commitment from US AI labs that's not yet spend until the data center is roll out.

you are conflating.

Deepseek and Muse are my go to for cheap. both work perfect for basic and mid tier tasks

Nvidia is also selling the shovle but they train their own LLM and by doing so they can fine tune their CUDA/Chip to have a better shovel than others.

Nvidia's own model does not have to beat OpenAI or any SOTA model. Nvidia just need to build up the in house expert and knowledge to make a better chip since hyperscalers and none hyperscaler like Meta is building their own AI chip now.

Apple can chose not to train their own model to learn how to sell a better shovel.

yes, this is my read as well. Nvidia does not care about how many LLM provider is out there as long as they pay the toll (Nvidia tax). for now, you can't beat the Nvidia CUDA/chip for training but for inference. that's where you can gain ground.

Hugging Face - distribution for model that you can run on your local Nvidia Spark

Neoclouds - Nvidia setup a 500 billion investment fund with Wall Street so Nvidia can sell chip and this news about buying a LLM start up. it seem like another customer for Nvidia.

correct me if i'm wrong but i remember i saw an interview with Jensen where he want more company to have their own model and country to have their own LLM model.

Nvidia doesn't make money from the gold rush. Nvidia made money from selling the shovels.

Nvidia is trying to increase its customer base. Look at the Mag 7, Amazon, Google, Microsoft, and even Meta are all working on their own inference chips. I don't think they can completely ditch Nvidia for LLM training, but they can make their own chips for inference. I believe that's also why OpenAI made its own.

No one wants to pay the Nvidia tax

maybe this is why Dario want to slow down AI development and all the big AI labs in the USA is singing the same song.

whey they all singing the same tune. it make me question what is their real motives.

they are afraid of Chinese good enough LLM model killing their margin. we already have story about US companies switch some task to use cheaper Chinese model hosted on Neoclouds.

>Nvidia’s financial engineering is partly a response to its biggest customers’ transformation into rivals. “Hyperscalers”, tech giants such as Amazon, Google, Meta and Microsoft, account for roughly half of Nvidia’s revenue

Companies just don't want to pay Jensen's tax. Hyperscalers might still pay Jensen's tax for LLM training but for inference. you don't have to. they are also betting on their own chip for training to replace Nvidia.

this is Nvidia panicking and doing vendor fiance to Neoclouds and buying Hugging Face. even none hyperscalers like Meta is betting on its own chip for AI inference.

it reminds me of a thread I read on PTT, Taiwan's Reddit. AI finally achieved what humans could not. Managers must give exact context for what they want, must pay exact wages (tokens), and can't delay salary payments (which seems to be a problem in China).

>I started using Spark 1.2 for development because if you're willing to let Meta train on your data it was dirt cheap

its free on opencode and i use it for personal projects. most of my personal projects are AI generated since its personal projects. nothing important are on them. it is hilarious if Meta is training their AI model with AI generated code.

>Musk admitted to distilling their models.

what's the moat for AI labs like OpenAI and Antrhopic as they seek trillion IPOs. a lot of people said Chinese models also distill US LLM models. if it is this easy to do. how do US AI labs justify asking for trillion?

A lot of the freakout and "bye" posts on the OpenCodeCLI subreddit due to DeepSeek raising prices.

Stripe is a middleman. So is OpenRouter. So is OpenCode. Unless you own the data center and the hardware, how cheap can a middleman's tokens really be compared to the hyperscalers, without massive model compression?

Even DeepSeek itself is raising token prices. How much margin is there for a middleman like Stripe buying tokens in bulk from a data center and reselling them? Last i check Stripe do not run or own physical data center

I doubt Stripe can do much better here.

OpenAI and Anthropic are both seeking trillion IPOs, while Chinese labs are pumping out open-weight models that are free for US providers to host and monetize.

These Chinese models cost less of US SOTA models to run, even if they are less capable. Providers can just run them, offer cheap tokens, and pocket the margin.

I just don't see how you justify a trillion valuation for US AI labs when the underlying models are being commoditized this fast.

agentic coding is real. If AI labs can take over the coding tool market, that's a billion+ market. LLMs work in coding, and AI labs can slowly expand into other white collar work. Vaporware? Hardly.

The American attitude is generally to let private companies build up a new industry so it can create jobs and pay taxes. However, in the LLM race, the Chinese open weight playbook pretty much killed that. China has basically commoditized LLMs. Chinese models are good enough, so the race has come down to who can offer the cheapest tokens.