diff --git a/.buildkite/vllm_lkg.version b/.buildkite/vllm_lkg.version
index 54b2b36583..5800c242dc 100644
--- a/.buildkite/vllm_lkg.version
+++ b/.buildkite/vllm_lkg.version
@@ -1 +1 @@
-64a40a7ab4d0053830fae04c83763fa67f2183e6
+010ec0c30ef1fa481fc69b8a5d2c205052d93607
diff --git a/tpu_inference/runner/multimodal_manager.py b/tpu_inference/runner/multimodal_manager.py
index fe616094e4..86aef70cb3 100644
--- a/tpu_inference/runner/multimodal_manager.py
+++ b/tpu_inference/runner/multimodal_manager.py
@@ -20,8 +20,6 @@
 from vllm.multimodal.inputs import MultiModalKwargsItem, PlaceholderRange
 from vllm.multimodal.utils import group_mm_kwargs_by_modality
 from vllm.v1.core.sched.output import SchedulerOutput as VllmSchedulerOutput
-from vllm.v1.worker.utils import (gather_mm_placeholders,
-                                  scatter_mm_placeholders)
 
 from tpu_inference.models.jax.utils.multi_modal_utils import (
     flatten_embeddings, sanity_check_mm_encoder_outputs)
@@ -160,15 +158,12 @@ def execute_mm_encoder(self, scheduler_output: "VllmSchedulerOutput"):
                 encoder_outputs.append(output)
 
         # Cache the encoder outputs.
-        for (mm_hash, pos_info), output in zip(
+        for (mm_hash, _), output in zip(
                 mm_hashes_pos,
                 encoder_outputs,
         ):
 
-            self.runner.encoder_cache[mm_hash] = scatter_mm_placeholders(
-                output,
-                is_embed=pos_info.is_embed,
-            )
+            self.runner.encoder_cache[mm_hash] = output
 
     def gather_mm_embeddings(self, scheduler_output: "VllmSchedulerOutput",
                              target_pad_len: int) -> list[jax.Array]:
@@ -201,6 +196,11 @@ def gather_mm_embeddings(self, scheduler_output: "VllmSchedulerOutput",
                     num_computed_tokens - start_pos + num_scheduled_tokens,
                     num_encoder_tokens)
                 assert start_idx < end_idx
+                curr_embeds_start, curr_embeds_end = (
+                    pos_info.get_embeds_indices_in_range(start_idx, end_idx))
+                if curr_embeds_start == curr_embeds_end:
+                    continue
+
                 mm_hash = mm_feature.identifier
                 encoder_output = self.runner.encoder_cache.get(mm_hash, None)
                 assert encoder_output is not None,\
@@ -209,11 +209,11 @@ def gather_mm_embeddings(self, scheduler_output: "VllmSchedulerOutput",
 
                 if (is_embed := pos_info.is_embed) is not None:
                     is_embed = is_embed[start_idx:end_idx]
+                    mm_embeds_item = encoder_output[
+                        curr_embeds_start:curr_embeds_end]
+                else:
+                    mm_embeds_item = encoder_output[start_idx:end_idx]
 
-                mm_embeds_item = gather_mm_placeholders(
-                    encoder_output[start_idx:end_idx],
-                    is_embed=is_embed,
-                )
                 mm_embeds.append(mm_embeds_item)
         if not mm_embeds:
             return None