SenseAuto's Sage with 3B active params claims to beat GPT-5.4 and Opus 4.6 in cars

3B激活参数，干翻GPT-5.4和Opus4.6，商汤绝影把龙虾塞进了车里

SenseAuto released Sage, an in-car multimodal edge model with 32B total params and 3B active params, and says it scored 94% on PinchBench, above Claude Opus 4.6 at 93.3% and GPT-5.4 at 90.5%. The post says Sage runs on Nvidia OrinX with about 0.5s TTFT, 0.03s TPOT, and 80 tok/s throughput; its SCOUT training method cuts GPU hours by about 60%, and ERL raises complex-task completion by 20%. The key point is not the headline race but whether a 3B-active model can sustain multi-step tool use on device.

Why it matters: HKR-H/K/R all pass: the 3B-active-vs-GPT hook is strong, and the post gives concrete OrinX latency, throughput, and benchmark numbers. I keep it at 79 because the evidence is self-reported and the impact is narrower than a general model launch.