diff --git a/src/lerobot/policies/pi052/modeling_pi052.py b/src/lerobot/policies/pi052/modeling_pi052.py
index ce8c3abc6..73799cbc9 100644
--- a/src/lerobot/policies/pi052/modeling_pi052.py
+++ b/src/lerobot/policies/pi052/modeling_pi052.py
@@ -55,6 +55,17 @@ from .configuration_pi052 import PI052Config
 logger = logging.getLogger(__name__)
 
 
+# FAST action-token vocab size (``lerobot/fast-action-tokenizer``). The
+# tokenizer maps a FAST BPE id ``t`` to the PaliGemma vocab id
+# ``vocab_size - 1 - fast_skip_tokens - t`` (see ``TokenizerProcessorStep``),
+# so action tokens occupy the top ``_FAST_ACTION_VOCAB_SIZE`` ids below the
+# ``fast_skip_tokens`` margin. The upper part collides with the reserved
+# ``<loc>`` block; the lower part sits just under it and otherwise leaks into
+# generated text as high-codepoint gibberish (the action-trained LM head puts
+# heavy mass on these ids), so ``select_message`` masks it.
+_FAST_ACTION_VOCAB_SIZE = 2048
+
+
 _HF_KERNELS_ENABLED = False
 
 
@@ -1166,6 +1177,15 @@ class PI052Policy(PI05Policy):
             if special_ids and len(generated) < min_new_tokens:
                 for sid in special_ids:
                     logits_step[..., sid] = float("-inf")
+            # Mask FAST action tokens that fall *below* the ``<loc>`` block.
+            # They are never valid text, but the action-trained head leaks
+            # them as gibberish; unlike the loc/seg block this region is never
+            # legitimately emitted (even by VQA), so suppress it on every call.
+            vocab_size = logits_step.shape[-1]
+            fast_skip = int(getattr(self.config, "fast_skip_tokens", 128))
+            fast_lo = vocab_size - 1 - fast_skip - (_FAST_ACTION_VOCAB_SIZE - 1)
+            if 0 < fast_lo < 256000:
+                logits_step[..., fast_lo:256000] = float("-inf")
             if suppress_loc_tokens:
                 logits_step[..., 256000:257024] = float("-inf")
             next_ids = self._sample_next_token(logits_step, temperature, top_p)