diff --git a/src/google/adk/models/anthropic_llm.py b/src/google/adk/models/anthropic_llm.py
index f6622628d6..3d6716e24f 100644
--- a/src/google/adk/models/anthropic_llm.py
+++ b/src/google/adk/models/anthropic_llm.py
@@ -709,6 +709,7 @@ def message_to_generate_content_response(
           role="model",
           parts=parts,
       ),
+      model_version=message.model,
       usage_metadata=usage_metadata,
       finish_reason=to_google_genai_finish_reason(message.stop_reason),
   )
@@ -1012,6 +1013,7 @@ async def _generate_content_streaming(
     cached_input_tokens: int | None = None
     cache_creation_tokens: int | None = None
     stop_reason: Optional[anthropic_types.StopReason] = None
+    model_version: str | None = None
 
     async for event in raw_stream:
       if event.type == "message_start":
@@ -1019,6 +1021,10 @@ async def _generate_content_streaming(
         output_tokens = event.message.usage.output_tokens
         thinking_tokens = _extract_thinking_token_count(event.message.usage)
         cached_input_tokens = _extract_cached_token_count(event.message.usage)
+        # Guard on str: keeps partial/mock streams that omit the field from
+        # poisoning model_version with a non-string.
+        if isinstance(event.message.model, str):
+          model_version = event.message.model
         cache_creation_tokens = _extract_cache_creation_token_count(
             event.message.usage
         )
@@ -1149,6 +1155,7 @@ async def _generate_content_streaming(
 
     yield LlmResponse(
         content=types.Content(role="model", parts=all_parts),
+        model_version=model_version,
         usage_metadata=usage_metadata,
         finish_reason=to_google_genai_finish_reason(stop_reason),
         partial=False,
diff --git a/tests/unittests/models/test_anthropic_llm.py b/tests/unittests/models/test_anthropic_llm.py
index 1f25a21700..41a524cf1f 100644
--- a/tests/unittests/models/test_anthropic_llm.py
+++ b/tests/unittests/models/test_anthropic_llm.py
@@ -16,7 +16,6 @@
 import json
 import os
 import re
-import sys
 from unittest import mock
 from unittest.mock import AsyncMock
 from unittest.mock import MagicMock
@@ -38,7 +37,6 @@
 from google.adk.models.llm_request import LlmRequest
 from google.adk.models.llm_response import LlmResponse
 from google.genai import types
-from google.genai import version as genai_version
 from google.genai.types import Content
 from google.genai.types import Part
 import httpx
@@ -3457,3 +3455,86 @@ def test_anthropic_config_allows_thinking_budget_without_thinking_level():
   assert config.effort == "high"
   assert config.thinking_config.thinking_budget == 2048
   assert config.thinking_config.thinking_level is None
+
+
+def test_message_to_generate_content_response_sets_model_version():
+  """The served snapshot id must land in LlmResponse.model_version (#6847)."""
+  from google.adk.models.anthropic_llm import (
+      message_to_generate_content_response,
+  )
+
+  message = anthropic_types.Message(
+      id="msg_model_version",
+      content=[
+          anthropic_types.TextBlock(text="ok", type="text", citations=None)
+      ],
+      model="claude-sonnet-4-20250514",
+      role="assistant",
+      stop_reason="end_turn",
+      stop_sequence=None,
+      type="message",
+      usage=anthropic_types.Usage(
+          input_tokens=1,
+          output_tokens=2,
+          cache_creation_input_tokens=0,
+          cache_read_input_tokens=0,
+          server_tool_use=None,
+          service_tier=None,
+      ),
+  )
+
+  response = message_to_generate_content_response(message)
+
+  assert response.model_version == "claude-sonnet-4-20250514"
+
+
+@pytest.mark.asyncio
+async def test_streaming_final_response_carries_model_version():
+  """Streaming: message_start's resolved model id reaches the final yield."""
+  llm = AnthropicLlm(model="claude-sonnet-4-20250514")
+
+  events = [
+      MagicMock(
+          type="message_start",
+          message=MagicMock(
+              model="claude-sonnet-4-20250514",
+              usage=MagicMock(input_tokens=10, output_tokens=0),
+          ),
+      ),
+      MagicMock(
+          type="content_block_start",
+          index=0,
+          content_block=anthropic_types.TextBlock(text="", type="text"),
+      ),
+      MagicMock(
+          type="content_block_delta",
+          index=0,
+          delta=anthropic_types.TextDelta(text="Hi!", type="text_delta"),
+      ),
+      MagicMock(type="content_block_stop", index=0),
+      MagicMock(
+          type="message_delta",
+          delta=MagicMock(stop_reason="end_turn"),
+          usage=MagicMock(output_tokens=3),
+      ),
+      MagicMock(type="message_stop"),
+  ]
+
+  mock_client = MagicMock()
+  mock_client.messages.create = AsyncMock(
+      return_value=_make_mock_stream_events(events)
+  )
+
+  llm_request = LlmRequest(
+      model="claude-sonnet-4-20250514",
+      contents=[Content(role="user", parts=[Part.from_text(text="Hi")])],
+  )
+
+  with mock.patch.object(llm, "_anthropic_client", mock_client):
+    responses = [
+        r async for r in llm.generate_content_async(llm_request, stream=True)
+    ]
+
+  final = responses[-1]
+  assert final.partial is False
+  assert final.model_version == "claude-sonnet-4-20250514"