diff --git a/vllm/v1/attention/backends/fa_utils.py b/vllm/v1/attention/backends/fa_utils.py
index 4039316c36c4..20502cbf0feb 100644
--- a/vllm/v1/attention/backends/fa_utils.py
+++ b/vllm/v1/attention/backends/fa_utils.py
@@ -4,6 +4,7 @@
 from typing import Any
 
 from vllm.logger import init_logger
+from vllm.model_executor.layers.batch_invariant import vllm_is_batch_invariant
 from vllm.platforms import current_platform
 
 logger = init_logger(__name__)
@@ -111,6 +112,16 @@ def get_flash_attn_version(
             )
             fa_version = 2
 
+        # FA4 currently uses batch-shape-dependent scheduling
+        # heuristics on SM100+, which breaks batch invariance.
+        if vllm_is_batch_invariant() and fa_version == 4:
+            logger.warning_once(
+                "Cannot use FA version 4 with batch invariance, "
+                "defaulting to FA version 2.",
+                scope="local",
+            )
+            fa_version = 2
+
         # FA4 on SM100 (Blackwell) has TMEM capacity limits that restrict
         # supported head dimensions.
         # See: https://github.com/Dao-AILab/flash-attention/issues/1959