Pequity Research, citing FundaAI, said GPT-6 used roughly 10 times the training compute of the GPT-5 generation. FundaAI also said that, based on industry discussions, the compute consumed by experiments, reinforcement learning, synthetic data generation and supporting infrastructure could amount to several times the main pre-training run, with the upper end reaching 10 times. It added that once TPU 8t and Vera Rubin ship at scale, the next round of pre-training acceleration could begin, with large-scale interconnect and optics set to benefit the most in that cycle. The note focuses on how total compute demand may extend well beyond the headline pre-training run and points to hardware delivery as a key condition for the next step in model training acceleration.
ChainCatcher reported that Pequity Research, citing FundaAI, said GPT-6 used about 10 times the training compute of the GPT-5 generation.
FundaAI said that, based on industry discussions, the compute consumed by experiments, reinforcement learning, synthetic data generation and related infrastructure could be several times larger than the main pre-training run, with the high end reaching 10 times.
Condition for the next pre-training acceleration cycle
FundaAI said that once TPU 8t and Vera Rubin begin shipping at scale, the next round of pre-training acceleration could start. In that cycle, large-scale interconnect and optics would benefit the most.
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