Groq recently released a new chip for large model inference, which can process 500 tokens per second, significantly surpassing traditional GPUs and Google TPUs. This breakthrough progress stems from the innovative design of the chip architecture by the Groq team and the deep technical accumulation of team members from Google TPU, including founder Jonathan Ross. This chip, which sells for about US$20,000, uses a self-developed LPU solution and plans to surpass Nvidia within three years, which will undoubtedly have a profound impact on the field of artificial intelligence.
Groq has launched a large model inference chip with a speed of 500 tokens per second, surpassing traditional GPU and Google TPU. Team members come from Google TPU, including founder Jonathan Ross. The chip uses a self-developed LPU solution and is committed to surpassing NVIDIA within three years, and the price is about US$20,000. It has extremely fast API access speed and support for multiple open source LLM models.
Groq's new chip is expected to become a strong competitor in the field of large model inference with its high-speed processing capabilities and support for a variety of open source models. Its extremely fast API access speed and competitive price will attract many developers and enterprise users and promote the further development of artificial intelligence applications. In the future, we will continue to pay attention to the progress of Groq and the changes its chips bring to the artificial intelligence industry.