China's DeepSeek chatbot reportedly gets much more done with fewer GPUs but Nvidia still thinks it's 'excellent' news
China's new DeepSeek R1 language model has been shaking things up by reportedly matching or even beating the performance of established rivals including OpenAI while using far fewer GPUs. Nvidia's response? R1 is «excellent» news that proves the need for even more of its AI-accelerating chips.
If you're thinking the math doesn't immediately add up, the stock market agrees, what with $600 billion being wiped off Nvidia's share price this week.
So, let's consider a few facts for a moment. Reuters reports that DeepSeek's development entailed 2,000 of Nvidia's H800 GPUs and a training budget of just $6 million, while CNBC claims that R1 «outperforms» the best LLMs from the likes of OpenAI and others.
The H800 is a special variant of Nvidia's Hopper H100 GPU that's been hobbled to fit within the US's export restriction rules for AI chips. Some in the AI industry claim that China generally and DeepSeek, in particular, have managed to dodge the export rules and acquire large numbers of Nvidia's more powerful H100 GPUs, but Nvidia has denied that claim.
Meanwhile, it's thought OpenAI used 25,000 of Nvidia's previous-gen A100 chips to train ChatGPT 4. It's hard to compare the A100 to the H800 directly, but it certainly seems like DeepSeek got more done with fewer GPUs.
That's why the market got the yips when it comes to Nvidia. Maybe we don't need quite as many chips for the AI revolution as was once thought?
Needless to say, Nvidia doesn't see it that way, lauding R1 for demonstrating how the so-called «Test Time» scaling technique can help create more powerful AI models. “DeepSeek is an excellent AI advancement and a perfect example of Test Time Scaling,” the company told CNBC. «DeepSeek’s work illustrates how new models can be created using that technique, leveraging widely-available models and compute that is fully export control compliant.»
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