Fix FP6-LLM benchmark

[gau-nernst]

Use the new user API for FP6-LLM benchmark.

4070 Ti SUPER

m	k	n	fp6_latency (ms)	fp16_latency (ms)	speedup (d/s)	correct
1	8192	8192	0.0259424	0.212709	8.1993	1
1	10240	8192	0.104522	0.265314	2.53835	1
1	57344	8192	0.558859	1.47519	2.63965	1
1	8192	28672	0.286704	0.756377	2.63818	1
2	8192	8192	0.0271974	0.225132	8.2777	1
2	10240	8192	0.105459	0.278289	2.63884	1
2	57344	8192	0.560128	1.51171	2.69886	1
2	8192	28672	0.290515	0.740313	2.54827	1
4	8192	8192	0.0341437	0.226175	6.62419	1
4	10240	8192	0.106526	0.278763	2.61686	1
4	57344	8192	0.562239	1.51169	2.6887	1
4	8192	28672	0.296588	0.741644	2.50059	1
8	8192	8192	0.0521865	0.228708	4.38251	1
8	10240	8192	0.108563	0.279899	2.57821	1
8	57344	8192	0.565344	1.51386	2.67776	1
8	8192	28672	0.305728	0.744223	2.43426	1
16	8192	8192	0.0684504	0.228147	3.33302	1
16	10240	8192	0.11321	0.281227	2.48413	1
16	57344	8192	0.571792	1.51852	2.65573	1
16	8192	28672	0.325349	0.748451	2.30046	1
32	8192	8192	0.0970511	0.226781	2.33671	1
32	10240	8192	0.125646	0.293164	2.33325	1
32	57344	8192	0.642472	1.59968	2.48989	1
32	8192	28672	0.368386	0.774405	2.10215	1
64	8192	8192	0.126184	0.230384	1.82577	1
64	10240	8192	0.155499	0.295118	1.89788	1
64	57344	8192	0.776818	1.61018	2.07278	1
64	8192	28672	0.487071	0.826973	1.69785	1
128	8192	8192	0.227225	0.246218	1.08359	1
128	10240	8192	0.281636	0.306252	1.0874	1
128	57344	8192	1.50182	1.69311	1.12737	1
128	8192	28672	0.971188	0.915551	0.942713	1
256	8192	8192	0.501718	0.396104	0.789494	1
256	10240	8192	0.603751	0.495955	0.821456	1
256	57344	8192	3.01183	2.81517	0.934703	1
256	8192	28672	1.85452	1.42665	0.769285	1
512	8192	8192	1.03497	0.793699	0.766883	1
512	10240	8192	1.24271	0.989675	0.796386	1
512	57344	8192	6.01086	5.47631	0.91107	1
512	8192	28672	3.41326	2.72313	0.797807	1

[pytorch-bot]

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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/312

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As of commit e12eb2f with merge base 12f44ab ():
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