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It took about a month for the finance world to start freaking out about DeepSeek, but when it did, it took more than half a trillion dollars - or one entire Stargate - off Nvidia's market cap. It wasn't just Nvidia, either: Tesla, Google, Amazon, and Microsoft tanked.
This is of course true. The sky-high valuations were irrational, and the drop was also irrational.
Even if critics are correct and DeepSeek isn't being truthful about what GPUs it has on hand (napkin math suggests the optimization techniques used means they are being truthful), it won't take long for the open-source community to find out, according to Hugging Face's head of research, Leandro von Werra. His team started working over the weekend to replicate and open-source the R1 recipe, and once researchers can create their own version of the model, "we're going to find out pretty quickly if numbers add up."
DeepSeek claims 100x improvements in training efficiency, but its published papers are full of micro-optimisations, which do not create 100x performance gains.
There are some people who are skeptical that DeepSeek's achievements were done in the way described. "We question the notion that its feats were done without the use of advanced GPUs to fine tune it and/or build the underlying LLMs the final model is based on," says Citi analyst Atif Malik in a research note. "It seems categorically false that 'China duplicated OpenAI for $5M' and we don't think it really bears further discussion," says Bernstein analyst Stacy Rasgon in her own note.
My take as well. DeepSeek did some useful work, and they published it. But there are very good reasons to believe that they didn't do everything they said - such as the fact that on release, DeepSeek was convinced it was ChatGPT.
Asus is already putting that CPU in a laptop, and owns Intel's NUC business, and a NUC with a Max+ 395 was spotted on the website of India's electronics regulator, so it definitely exists now, and we just don't know if and when it will arrive on the market.