3/ The clearest evidence: token efficiency. On Artificial Analysis, Muse Spark achieves similar results to leading models using far fewer tokens. Wang suspects competitors have "some level of fundamental inefficiency at another part of the stack that gets patched by enabling the models to think longer." Said differently, some labs are using brute-force reasoning tokens to compensate for architectural debt. MSL's clean stack avoids that tax.