The True Cost of Compute
a16z Podcast
The Cost of Training Large Language Models
Training large language models, like GPT-3 with 175 billion parameters, involves about 3 x 10^23 floating point operations, which is an immense computational challenge. Using an A100 card, the estimated cost for training such models is around half a million dollars, but this is a simplistic analysis. In reality, factoring in optimization, memory bandwidth limitations, network restrictions, and multiple test runs, the actual cost escalates to millions of dollars, often in the tens of millions range. The need for reserve capacity further elevates the cost, making it a substantial investment.
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