diff --git a/vllm/model_executor/layers/quantization/compressed_tensors/compressed_tensors_moe/compressed_tensors_moe_w4a8_fp8.py b/vllm/model_executor/layers/quantization/compressed_tensors/compressed_tensors_moe/compressed_tensors_moe_w4a8_fp8.py
index 74cb0b4f6e..ab805591de 100644
--- a/vllm/model_executor/layers/quantization/compressed_tensors/compressed_tensors_moe/compressed_tensors_moe_w4a8_fp8.py
+++ b/vllm/model_executor/layers/quantization/compressed_tensors/compressed_tensors_moe/compressed_tensors_moe_w4a8_fp8.py
@@ -198,11 +198,15 @@ class CompressedTensorsW4A8Fp8MoEMethod(CompressedTensorsMoEMethod):
         # encode and reorder weight tensors, and get the layout to pass to
         # the grouped gemm kernel. `b_strides1/2` specifies the entire layout
         convert_packed_uint4b8_to_signed_int4_inplace(layer.w13_weight_packed)
+        # mirror the sync in CutlassW4A8LinearKernel; required for tp>1 correctness
+        torch.accelerator.synchronize()
         w13_weight_shuffled, self.b_strides1 = (
             ops.cutlass_encode_and_reorder_int4b_grouped(layer.w13_weight_packed)
         )
         replace_parameter(layer, "w13_weight_packed", w13_weight_shuffled)
         convert_packed_uint4b8_to_signed_int4_inplace(layer.w2_weight_packed)
+        # mirror the sync in CutlassW4A8LinearKernel; required for tp>1 correctness
+        torch.accelerator.synchronize()
         w2_weight_shuffled, self.b_strides2 = (
             ops.cutlass_encode_and_reorder_int4b_grouped(layer.w2_weight_packed)
         )
diff --git a/vllm/model_executor/layers/quantization/utils/quant_utils.py b/vllm/model_executor/layers/quantization/utils/quant_utils.py
index d1b1b77988..de76deb191 100644
--- a/vllm/model_executor/layers/quantization/utils/quant_utils.py
+++ b/vllm/model_executor/layers/quantization/utils/quant_utils.py
@@ -818,7 +818,7 @@ def convert_bf16_scales_to_fp8(
 
     # restore original shape
     fp8_scales = fp8_scales.view(orig_shape)
-    chan_scales = chan_scales.view(orig_shape[:-1], -1)
+    chan_scales = chan_scales.view(*orig_shape[:-1], -1)
 
     return fp8_scales, chan_scales