Behind the Parameter Leap in Chinese AI Models
soumitrashukla9 · x · 2026-07-20
The reposted content discusses why Chinese models suddenly jumped from 800-1000B parameters to a massive 2.4-2.8T.
The author judges that a scale leap like this usually implies a new hardware/compute unlock behind the scenes; otherwise, both training and inference for such large models would be extremely difficult. The implication is that over the past six months, it's not that they "suddenly got better at training models," but rather that infrastructure conditions changed.
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