The gap between closed and open models might be much smaller than commonly assumed, because we don’t know what closed model providers do *in addition to* model inference

When Claude dominates GLM-5.2 in benchmarks, it’s usually assumed that Anthropic has superior model architectures, superior training pipelines, and other advanced machine learning techniques that make their models better than the competition. But actually, this doesn’t follow. Because the benchmarks compare model inference on GLM with the whole Claude product, and we don’t know what that product does behind the scenes. Anthropic already re