Artificial intelligence (AI) chips from Qualcomm Inc beat Nvidia Corp in two out of three measures of power efficiency in a new set of test data published on Wednesday, while a Taiwanese start-up bested both in one category.
Nvidia dominates the market for training AI models, but after AI models are trained, they are put to wider use in “inference” by doing tasks such as generating text responses and analyzing images.
Analysts say that the market for data center inference chips would grow quickly as businesses put AI technologies into their products, but companies such as Alphabet Inc’s Google are already exploring how to keep the lid on the extra costs that doing so would add.
Photo: Reuters
Qualcomm has created a chip called the Cloud AI 100 that aims for parsimonious power consumption.
In testing data published on Wednesday by MLCommons, an engineering consortium that maintains testing benchmarks widely used in the AI chip industry, Qualcomm’s AI 100 beat Nvidia’s flagship H100 chip at classifying images, based on how many data center server queries each chip can carry out per watt.
Qualcomm’s chips hit 197.6 server queries per watt versus 108.4 queries per watt for Nvidia.
Neuchips Corp (創鑫智慧), a start-up founded by veteran Taiwanese chip academic Lin Youn-long (林永隆), took the top spot with 227 queries per watt.
Qualcomm also beat Nvidia at object detection with a score of 3.2 queries per watt versus Nvidia’s 2.4 queries per watt.
Object detection can be used in applications such as analyzing footage from retail stores to see where shoppers go most often.
However, Nvidia took the top spot in absolute performance terms and power efficiency terms in a test of natural-language processing, the AI technology most widely used in chatbots.
Nvidia hit 10.8 samples per watt, while Neuchips ranked second at 8.9 samples per watt and Qualcomm was third at 7.5 samples per watt.
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