Outline In this study, we explore the performance limits of these TAGE-SC-L predictors for respectively 8Kbytes and 64Kbytes of storage budget. For a 8KB storage budget, our submitted predictor used most of its storage budget on the TAGE predictor, features a very small loop predictor LP and a neural statistical cor-rector exploiting global history path and very limited local history. The submitted 8Kbytes predictor achieves 4.991 MPKI on the CBP-5 train traces. With a larger storage budget, one can invest more significant storage budget in the adjunct predictors. The submitted 512Kbits TAGE-SC-L predictor features a TAGE predictor, a loop predictor LP and a quite complex (57 Kbits) neural statistical corrector that exploits various form of local histories , global branch history, IMLI counter [12]. The submitted 64KB TAGE-SC-L predictor achieves 3.986 MPKI on the CBP-5 train traces.