--- a/vllm/model_executor/layers/sparse_attn_indexer.py
+++ b/vllm/model_executor/layers/sparse_attn_indexer.py
@@ -1,6 +1,8 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """Custom Sparse Attention Indexer layers."""
+
+import os
 
 import torch
 import torch.distributed as dist
@@ -286,6 +288,29 @@
     return q_fp8, weights_out
 
 
+# PF1: keep the legacy layout unless explicitly enabled for a measured A/B.
+_DSV41_INDEXER_REQUEST_WORKSPACE = (
+    os.environ.get("VLLM_DSV41_INDEXER_REQUEST_WORKSPACE", "0") == "1"
+)
+
+
+def _prefill_workspace_rows(reserved_rows: int, chunk_rows: list[int]) -> int:
+    """Host-known maximum gather extent, including query-continuation chunks.
+
+    The profile reservation stays unchanged. All views are made once before
+    the loop so skip_kv_gather continuations reuse the same values AND scales.
+    No device scalar read, reallocation, altered split or changed kernel shape.
+    """
+    if reserved_rows < 0 or any(rows < 0 for rows in chunk_rows):
+        raise ValueError("Indexer prefill workspace row counts must be nonnegative")
+    rows = max(chunk_rows, default=0)
+    if rows > reserved_rows:
+        raise ValueError(
+            f"Indexer prefill gather needs {rows} rows, reservation is {reserved_rows}"
+        )
+    return rows
+
+
 def _gather_workspace_shapes(
     total_seq_lens: int,
     head_dim: int,
@@ -573,8 +598,17 @@
         # MXFP4 (head_dim/2 bytes packed + head_dim/MXFP4_BLOCK_SIZE ue8m0
         # scales) based on use_fp4_cache.
         workspace_manager = current_workspace_manager()
+        # PF1: on the served TP-only path, use the actual largest gather
+        # for the workspace views and scale offset, independent of model cap.
+        # Keep PCP/DCP and the dummy/profile reservation on the legacy layout.
+        gather_rows = total_seq_lens
+        if _DSV41_INDEXER_REQUEST_WORKSPACE and not use_pcp and dcp_world_size == 1:
+            gather_rows = _prefill_workspace_rows(
+                total_seq_lens,
+                [chunk.max_local_total_seq_lens for chunk in prefill_metadata.chunks],
+            )
         values_spec, scales_spec = _gather_workspace_shapes(
-            total_seq_lens, head_dim, fp8_dtype, use_fp4_cache
+            gather_rows, head_dim, fp8_dtype, use_fp4_cache
         )
         # PCP + DCP needs two more pairs: the rank-major all-gather destination
         # and the de-interleaved result.