[Perf]Remove H2D for Qwen3.5 SpecV2 (#20864)

python/sglang/srt/model_executor/forward_batch_info.py

@@ -715,9 +715,15 @@ class ForwardBatch(ForwardBatchDeepSeekMHAMixin):
 
         else:  # target_verify or draft_decode
             seq_positions = batch.spec_info.positions.view(batch_size, -1)
+            # Split text-only and mixed batches here because SpecV2 text-only batches can avoid an extra D2H.
+            if all(mm_input is None for mm_input in mm_inputs):
+                mrope_delta_tensor = torch.zeros(
+                    (batch_size, 1), dtype=torch.int64, device=device
+                )
+            else:
                 mrope_deltas = [
                     (
-                    torch.tensor([0], dtype=torch.int64)
+                        torch.zeros(1, dtype=torch.int64)
                         if mm_inputs[i] is None
                         else mm_inputs[i].mrope_position_delta.squeeze(0)
                     )

python/sglang/srt/speculative/eagle_info_v2.py

@@ -234,14 +234,12 @@ class EagleVerifyInputV2Mixin:
 
             # Set mamba_track_indices for mamba prefix-cache state tracking
             if get_global_server_args().enable_mamba_extra_buffer():
-                batch.mamba_track_indices = torch.tensor(
+                batch.mamba_track_indices = torch.stack(
                     [
                         req.mamba_ping_pong_track_buffer[req.mamba_next_track_idx]
                         for req in batch.reqs
-                    ],
-                    dtype=torch.int64,
-                    device=device,
-                )
+                    ]
+                ).to(torch.int64)
                 batch.mamba_track_mask = None
                 batch.mamba_track_seqlens = None