This is a cookie cutter comment that appears to have been copy pasted from a thread about Gamestop or something. DeepSeek R1 allegedly being almost 50x more compute efficient isn't just a "vague rumor". You do this community a disservice by commenting before understanding what investors are thinking at the current moment.
Has anyone verified DeepSeek's claims about R1? They have literally published one single paper and it has been out for a week. Nothing about what they did changed Nvidia's fundamentals. In fact there was no additional news over the weekend or today morning. The entire market movement is because of a single statement by DeepSeek's CEO from over a week ago. People sold because other people sold. This is exactly how a panic selloff happens.
They have not verified the claims but those claims are not a "vague rumor". Expectations of discounted cash flows, which is primarily what drives large cap stock prices, operates on probability, not strange notions of "we must be absolutely certain that something is true".
A credible lab making a credible claim to massive efficiency improvements is a credible threat to Nvidia's future earnings. Hence the stock got sold. It's not more complicated than that.
Not a true verification but I have tried the Deepseek R1 7b model running locally, it runs on my 6gb laptop GPU and the results are impressive.
Its obviously constrained by this hardware and this model size as it does some strange things sometimes and it is slow (30 secs to respond) but I've got it to do some impressive things that GPT4 struggles with or fails on.
Also of note I asked it about Taiwan and it parroted the official CCP line about Taiwan being part of China, without even the usual delay while it generated the result.
The weights are public. We can't verify their claims about the amount of compute used for training, but we can trivially verify the claims about inference cost and benchmark performance. On both those counts, DeepSeek have been entirely honest.
Benchmark performance - better models are actually great for Nvidia's bottom line, since the company is relying on the advancement of AI as a whole.
Inference cost - DeepSeek is charging less than OpenAI to use its public API, but that isn't an indicator of anything since it doesn't reflect the actual cost of operation. It's pretty much a guarantee that both companies are losing money. Looking at DeepSeek's published models the inference cost is in the same ballpark as Llama and the rest.
Which leaves training, and that's what all the speculation is about. The CEO said that the model cost $5.5M and that's what the entire world is clinging on. We have literally no other info and no way to verify it (for now, until efforts to replicate it start to show results).
>Inference cost - DeepSeek is charging less than OpenAI to use its public API, but that isn't an indicator of anything since it doesn't reflect the actual cost of operation.
Again, the weights are public. You can run the full-fat version of R1 on your own hardware, or a cloud provider of your choice. The inference costs match what DeepSeek are claiming, for reasons that are entirely obvious based on the architecture. Either the incumbents are secretly making enormous margins on inference, or they're vastly less efficient; in the first case they're in trouble, in the second case they're in real trouble.
R1's inference costs are in the same ballpark as Llama 3 and every other similar model in its class. People are just reading and repeating "it is cheap!!" ad nauseam without any actual data to back it up.
is llama405 a distilled model like DeepSeek or a trained frontier model? I honestly ask because I haven't researched but that's important to know before one compares.
