diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/streaming_iterator.py b/litellm/llms/anthropic/experimental_pass_through/adapters/streaming_iterator.py
index 44c367ee805..3aec95f5c02 100644
--- a/litellm/llms/anthropic/experimental_pass_through/adapters/streaming_iterator.py
+++ b/litellm/llms/anthropic/experimental_pass_through/adapters/streaming_iterator.py
@@ -402,7 +402,9 @@ class AnthropicStreamWrapper(AdapterCompletionStreamWrapper):
                 will_merge_into_held = (
                     self.holding_stop_reason_chunk is not None and getattr(chunk, "usage", None) is not None
                 )
-                is_final_chunk = chunk.choices[0].finish_reason is not None
+                is_final_chunk = (
+                    bool(chunk.choices) and chunk.choices[0].finish_reason is not None
+                )
                 processed_chunk = LiteLLMAnthropicMessagesAdapter().translate_streaming_openai_response_to_anthropic(
                     response=chunk,
                     current_content_block_index=self.current_content_block_index,
@@ -622,7 +624,9 @@ class AnthropicStreamWrapper(AdapterCompletionStreamWrapper):
                 will_merge_into_held = (
                     self.holding_stop_reason_chunk is not None and getattr(chunk, "usage", None) is not None
                 )
-                is_final_chunk = chunk.choices[0].finish_reason is not None
+                is_final_chunk = (
+                    bool(chunk.choices) and chunk.choices[0].finish_reason is not None
+                )
                 processed_chunk = LiteLLMAnthropicMessagesAdapter().translate_streaming_openai_response_to_anthropic(
                     response=chunk,
                     current_content_block_index=self.current_content_block_index,
@@ -852,6 +856,10 @@ class AnthropicStreamWrapper(AdapterCompletionStreamWrapper):
         from .transformation import LiteLLMAnthropicMessagesAdapter
 
         # Example logic - customize based on your needs:
+        # Usage-only / keepalive chunks carry no choices (choices=[]) — they
+        # don't open a new content block. See #30761.
+        if not chunk.choices:
+            return False
         # If chunk indicates a tool call
         if chunk.choices[0].finish_reason is not None:
             return False
diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
index 02625605f37..37b8813d499 100644
--- a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
@@ -1480,11 +1480,17 @@ class LiteLLMAnthropicMessagesAdapter:
         current_content_block_index: int,
         applied_edits: Optional[List[AppliedEdit]] = None,
     ) -> Union[ContentBlockDelta, MessageBlockDelta]:
-        ## base case - final chunk w/ finish reason
-        if response.choices[0].finish_reason is not None:
-            delta = MessageDelta(
-                stop_reason=self._translate_openai_finish_reason_to_anthropic(response.choices[0].finish_reason),
+        ## base case - final chunk w/ finish reason, or a usage-only chunk
+        ## (choices=[]) that carries trailing usage. See #30761.
+        if not response.choices or response.choices[0].finish_reason is not None:
+            stop_reason = (
+                self._translate_openai_finish_reason_to_anthropic(
+                    response.choices[0].finish_reason
+                )
+                if response.choices
+                else None
             )
+            delta = MessageDelta(stop_reason=stop_reason)
             if getattr(response, "usage", None) is not None:
                 litellm_usage_chunk: Optional[Usage] = response.usage  # type: ignore
             elif hasattr(response, "_hidden_params") and "usage" in response._hidden_params:
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_streaming_iterator_empty_choices.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_streaming_iterator_empty_choices.py
new file mode 100644
index 00000000000..04068534885
--- /dev/null
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_streaming_iterator_empty_choices.py
@@ -0,0 +1,79 @@
+"""Regression test for #30761 — the Anthropic streaming bridge crashed with
+IndexError when an upstream OpenAI/Azure-compatible chunk had choices=[]
+(usage-only / keepalive chunk)."""
+
+import os
+import sys
+from typing import List, Optional
+from unittest.mock import MagicMock
+
+import pytest
+
+sys.path.insert(0, os.path.abspath("../../../../.."))
+
+from litellm.llms.anthropic.experimental_pass_through.adapters.streaming_iterator import (
+    AnthropicStreamWrapper,
+)
+from litellm.types.utils import Delta, StreamingChoices, Usage
+
+
+def _content_chunk(text: str, finish_reason: Optional[str] = None) -> MagicMock:
+    chunk = MagicMock()
+    chunk.choices = [
+        StreamingChoices(
+            finish_reason=finish_reason,
+            index=0,
+            delta=Delta(content=text),
+            logprobs=None,
+        )
+    ]
+    chunk.usage = None
+    chunk._hidden_params = {}
+    return chunk
+
+
+def _usage_only_chunk() -> MagicMock:
+    # OpenAI include_usage trailing chunk: empty choices, usage set
+    chunk = MagicMock()
+    chunk.choices = []
+    chunk.usage = Usage(prompt_tokens=5, completion_tokens=3, total_tokens=8)
+    chunk._hidden_params = {}
+    return chunk
+
+
+def test_sync_stream_survives_empty_choices_usage_chunk():
+    chunks = [
+        _content_chunk("hi"),
+        _content_chunk("", finish_reason="stop"),
+        _usage_only_chunk(),
+    ]
+    wrapper = AnthropicStreamWrapper(completion_stream=iter(chunks), model="claude-x")
+    events = list(wrapper)  # used to raise IndexError mid-stream
+    assert events
+
+
+@pytest.mark.asyncio
+async def test_async_stream_survives_empty_choices_usage_chunk():
+    class _AsyncStream:
+        def __init__(self, items):
+            self._it = iter(items)
+
+        def __aiter__(self):
+            return self
+
+        async def __anext__(self):
+            try:
+                return next(self._it)
+            except StopIteration:
+                raise StopAsyncIteration
+
+    chunks = [
+        _content_chunk("hi"),
+        _content_chunk("", finish_reason="stop"),
+        _usage_only_chunk(),
+    ]
+    wrapper = AnthropicStreamWrapper(
+        completion_stream=_AsyncStream(chunks), model="claude-x"
+    )
+    events = [e async for e in wrapper]
+    assert events