Use Cute-DSL MXFP8 quantize kernels (#25486)

Co-authored-by: b8zhong <b8zhong@users.noreply.github.com>

python/sglang/srt/layers/quantization/mxfp4_flashinfer_trtllm_moe.py

@@ -21,7 +21,9 @@ from sglang.srt.utils import (
     log_info_on_rank0,
     set_weight_attrs,
 )
-from sglang.srt.utils.common import next_power_of_2
+from sglang.srt.utils.common import is_sm100_supported, next_power_of_2
+
+_MXFP8_QUANTIZE_BACKEND = "cute-dsl" if is_sm100_supported() else "cuda"
 
 if is_flashinfer_available():
     from flashinfer import mxfp8_quantize, shuffle_matrix_a, shuffle_matrix_sf_a
@@ -379,7 +381,10 @@ class Mxfp4FlashinferTrtllmMoEMethod:
                 )
         elif precision == "default":
             x_quant, x_scale = mxfp8_quantize(
-                hidden_states, False, alignment=hidden_size
+                hidden_states,
+                False,
+                alignment=hidden_size,
+                backend=_MXFP8_QUANTIZE_BACKEND,
             )
             x_scale = x_scale.view(torch.float8_e4m3fn).reshape(
                 *hidden_states.shape[:-1], -1