diff --git a/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_handler.py b/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_handler.py
index 11d4d0b92f6..bd750a47f63 100644
--- a/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_handler.py
+++ b/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_handler.py
@@ -1844,127 +1844,6 @@ def test_streaming_code_execution_produces_code_interpreter_results():
     )
 
 
-def test_anthropic_streaming_thinking_text_tool_use_sync():
-    sse_lines = [
-        b"event: message_start\n",
-        b'data: {"type":"message_start","message":{"id":"msg_test_123","type":"message","role":"assistant","model":"claude-3-7-sonnet-20250219","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":10,"output_tokens":1}}}\n',
-        b"\n",
-        b"event: content_block_start\n",
-        b'data: {"type":"content_block_start","index":0,"content_block":{"type":"thinking","thinking":""}}\n',
-        b"\n",
-        b"event: content_block_delta\n",
-        b'data: {"type":"content_block_delta","index":0,"delta":{"type":"thinking_delta","thinking":"Let me call submit_result"}}\n',
-        b"\n",
-        b"event: content_block_stop\n",
-        b'data: {"type":"content_block_stop","index":0}\n',
-        b"\n",
-        b"event: content_block_start\n",
-        b'data: {"type":"content_block_start","index":1,"content_block":{"type":"text","text":""}}\n',
-        b"\n",
-        b"event: content_block_delta\n",
-        b'data: {"type":"content_block_delta","index":1,"delta":{"type":"text_delta","text":"I will now submit the result."}}\n',
-        b"\n",
-        b"event: content_block_stop\n",
-        b'data: {"type":"content_block_stop","index":1}\n',
-        b"\n",
-        b"event: content_block_start\n",
-        b'data: {"type":"content_block_start","index":2,"content_block":{"type":"tool_use","id":"toolu_01","name":"submit_result","input":{}}}\n',
-        b"\n",
-        b"event: content_block_delta\n",
-        b'data: {"type":"content_block_delta","index":2,"delta":{"type":"input_json_delta","partial_json":"{\\"value\\":"}}\n',
-        b"\n",
-        b"event: content_block_delta\n",
-        b'data: {"type":"content_block_delta","index":2,"delta":{"type":"input_json_delta","partial_json":"1}"}}\n',
-        b"\n",
-        b"event: content_block_stop\n",
-        b'data: {"type":"content_block_stop","index":2}\n',
-        b"\n",
-        b"event: message_delta\n",
-        b'data: {"type":"message_delta","delta":{"stop_reason":"tool_use","stop_sequence":null},"usage":{"output_tokens":25}}\n',
-        b"\n",
-        b"event: message_stop\n",
-        b'data: {"type":"message_stop"}\n',
-    ]
-
-    iterator = ModelResponseIterator(
-        streaming_response=iter(sse_lines),
-        sync_stream=True,
-        json_mode=False,
-    )
-    chunks = list(iterator)
-
-    assert all(isinstance(c, litellm.ModelResponseStream) for c in chunks)
-
-    tool_call_chunks = [c for c in chunks if getattr(c.choices[0].delta, "tool_calls", None) is not None]
-    assert len(tool_call_chunks) == 3
-    assert tool_call_chunks[0].choices[0].delta.tool_calls[0].function.name == "submit_result"
-    assert tool_call_chunks[0].choices[0].delta.tool_calls[0].id == "toolu_01"
-
-    built = litellm.stream_chunk_builder(chunks=chunks)
-    assert built.choices[0].message.content == "I will now submit the result."
-    assert built.choices[0].message.tool_calls is not None
-    assert len(built.choices[0].message.tool_calls) == 1
-    assert built.choices[0].message.tool_calls[0].function.name == "submit_result"
-    assert built.choices[0].message.tool_calls[0].function.arguments == '{"value":1}'
-    assert built.choices[0].finish_reason == "tool_calls"
-
-
-@pytest.mark.asyncio
-async def test_anthropic_streaming_thinking_text_tool_use_async():
-    sse_lines = [
-        "event: message_start\n",
-        'data: {"type":"message_start","message":{"id":"msg_async_123","type":"message","role":"assistant","model":"claude-3-7-sonnet-20250219","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":10,"output_tokens":1}}}\n',
-        "event: content_block_start\n",
-        'data: {"type":"content_block_start","index":0,"content_block":{"type":"thinking","thinking":""}}\n',
-        "event: content_block_delta\n",
-        'data: {"type":"content_block_delta","index":0,"delta":{"type":"thinking_delta","thinking":"Async thinking..."}}\n',
-        "event: content_block_stop\n",
-        'data: {"type":"content_block_stop","index":0}\n',
-        "event: content_block_start\n",
-        'data: {"type":"content_block_start","index":1,"content_block":{"type":"tool_use","id":"toolu_async_01","name":"do_action","input":{}}}\n',
-        "event: content_block_delta\n",
-        'data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":"{\\"action\\": \\"run\\"}"}}\n',
-        "event: content_block_stop\n",
-        'data: {"type":"content_block_stop","index":1}\n',
-        "event: message_delta\n",
-        'data: {"type":"message_delta","delta":{"stop_reason":"tool_use","stop_sequence":null},"usage":{"output_tokens":15}}\n',
-        "event: message_stop\n",
-        'data: {"type":"message_stop"}\n',
-    ]
-
-    class AsyncLineIterator:
-        def __init__(self, lines):
-            self._iter = iter(lines)
-
-        def __aiter__(self):
-            return self
-
-        async def __anext__(self):
-            try:
-                return next(self._iter)
-            except StopIteration:
-                raise StopAsyncIteration
-
-    iterator = ModelResponseIterator(
-        streaming_response=AsyncLineIterator(sse_lines),
-        sync_stream=False,
-        json_mode=False,
-    )
-
-    chunks = []
-    async for chunk in iterator:
-        chunks.append(chunk)
-
-    assert all(isinstance(c, litellm.ModelResponseStream) for c in chunks)
-    tool_call_chunks = [c for c in chunks if getattr(c.choices[0].delta, "tool_calls", None) is not None]
-    assert len(tool_call_chunks) == 2
-    assert tool_call_chunks[0].choices[0].delta.tool_calls[0].function.name == "do_action"
-
-    built = litellm.stream_chunk_builder(chunks=chunks)
-    assert built.choices[0].message.tool_calls[0].function.name == "do_action"
-    assert json.loads(built.choices[0].message.tool_calls[0].function.arguments) == {"action": "run"}
-
-
 def test_streaming_multiple_code_executions_no_duplicates():
     """
     Test that multiple code executions in a single streaming response emit
diff --git a/tests/unit/llms/anthropic/chat/test_anthropic_sse_framing.py b/tests/unit/llms/anthropic/chat/test_anthropic_sse_framing.py
new file mode 100644
index 00000000000..fc97edf246e
--- /dev/null
+++ b/tests/unit/llms/anthropic/chat/test_anthropic_sse_framing.py
@@ -0,0 +1,127 @@
+import json
+
+import pytest
+
+import litellm
+from litellm.llms.anthropic.chat.handler import ModelResponseIterator
+
+
+def test_anthropic_streaming_thinking_text_tool_use_sync():
+    sse_lines = [
+        b"event: message_start\n",
+        b'data: {"type":"message_start","message":{"id":"msg_test_123","type":"message","role":"assistant","model":"claude-3-7-sonnet-20250219","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":10,"output_tokens":1}}}\n',
+        b"\n",
+        b"event: content_block_start\n",
+        b'data: {"type":"content_block_start","index":0,"content_block":{"type":"thinking","thinking":""}}\n',
+        b"\n",
+        b"event: content_block_delta\n",
+        b'data: {"type":"content_block_delta","index":0,"delta":{"type":"thinking_delta","thinking":"Let me call submit_result"}}\n',
+        b"\n",
+        b"event: content_block_stop\n",
+        b'data: {"type":"content_block_stop","index":0}\n',
+        b"\n",
+        b"event: content_block_start\n",
+        b'data: {"type":"content_block_start","index":1,"content_block":{"type":"text","text":""}}\n',
+        b"\n",
+        b"event: content_block_delta\n",
+        b'data: {"type":"content_block_delta","index":1,"delta":{"type":"text_delta","text":"I will now submit the result."}}\n',
+        b"\n",
+        b"event: content_block_stop\n",
+        b'data: {"type":"content_block_stop","index":1}\n',
+        b"\n",
+        b"event: content_block_start\n",
+        b'data: {"type":"content_block_start","index":2,"content_block":{"type":"tool_use","id":"toolu_01","name":"submit_result","input":{}}}\n',
+        b"\n",
+        b"event: content_block_delta\n",
+        b'data: {"type":"content_block_delta","index":2,"delta":{"type":"input_json_delta","partial_json":"{\\"value\\":"}}\n',
+        b"\n",
+        b"event: content_block_delta\n",
+        b'data: {"type":"content_block_delta","index":2,"delta":{"type":"input_json_delta","partial_json":"1}"}}\n',
+        b"\n",
+        b"event: content_block_stop\n",
+        b'data: {"type":"content_block_stop","index":2}\n',
+        b"\n",
+        b"event: message_delta\n",
+        b'data: {"type":"message_delta","delta":{"stop_reason":"tool_use","stop_sequence":null},"usage":{"output_tokens":25}}\n',
+        b"\n",
+        b"event: message_stop\n",
+        b'data: {"type":"message_stop"}\n',
+    ]
+
+    iterator = ModelResponseIterator(
+        streaming_response=iter(sse_lines),
+        sync_stream=True,
+        json_mode=False,
+    )
+    chunks = list(iterator)
+
+    assert all(isinstance(c, litellm.ModelResponseStream) for c in chunks)
+
+    tool_call_chunks = [c for c in chunks if getattr(c.choices[0].delta, "tool_calls", None) is not None]
+    assert len(tool_call_chunks) == 3
+    assert tool_call_chunks[0].choices[0].delta.tool_calls[0].function.name == "submit_result"
+    assert tool_call_chunks[0].choices[0].delta.tool_calls[0].id == "toolu_01"
+
+    built = litellm.stream_chunk_builder(chunks=chunks)
+    assert built.choices[0].message.content == "I will now submit the result."
+    assert built.choices[0].message.tool_calls is not None
+    assert len(built.choices[0].message.tool_calls) == 1
+    assert built.choices[0].message.tool_calls[0].function.name == "submit_result"
+    assert built.choices[0].message.tool_calls[0].function.arguments == '{"value":1}'
+    assert built.choices[0].finish_reason == "tool_calls"
+
+
+@pytest.mark.asyncio
+async def test_anthropic_streaming_thinking_text_tool_use_async():
+    sse_lines = [
+        "event: message_start\n",
+        'data: {"type":"message_start","message":{"id":"msg_async_123","type":"message","role":"assistant","model":"claude-3-7-sonnet-20250219","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":10,"output_tokens":1}}}\n',
+        "event: content_block_start\n",
+        'data: {"type":"content_block_start","index":0,"content_block":{"type":"thinking","thinking":""}}\n',
+        "event: content_block_delta\n",
+        'data: {"type":"content_block_delta","index":0,"delta":{"type":"thinking_delta","thinking":"Async thinking..."}}\n',
+        "event: content_block_stop\n",
+        'data: {"type":"content_block_stop","index":0}\n',
+        "event: content_block_start\n",
+        'data: {"type":"content_block_start","index":1,"content_block":{"type":"tool_use","id":"toolu_async_01","name":"do_action","input":{}}}\n',
+        "event: content_block_delta\n",
+        'data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":"{\\"action\\": \\"run\\"}"}}\n',
+        "event: content_block_stop\n",
+        'data: {"type":"content_block_stop","index":1}\n',
+        "event: message_delta\n",
+        'data: {"type":"message_delta","delta":{"stop_reason":"tool_use","stop_sequence":null},"usage":{"output_tokens":15}}\n',
+        "event: message_stop\n",
+        'data: {"type":"message_stop"}\n',
+    ]
+
+    class AsyncLineIterator:
+        def __init__(self, lines):
+            self._iter = iter(lines)
+
+        def __aiter__(self):
+            return self
+
+        async def __anext__(self):
+            try:
+                return next(self._iter)
+            except StopIteration:
+                raise StopAsyncIteration
+
+    iterator = ModelResponseIterator(
+        streaming_response=AsyncLineIterator(sse_lines),
+        sync_stream=False,
+        json_mode=False,
+    )
+
+    chunks = []
+    async for chunk in iterator:
+        chunks.append(chunk)
+
+    assert all(isinstance(c, litellm.ModelResponseStream) for c in chunks)
+    tool_call_chunks = [c for c in chunks if getattr(c.choices[0].delta, "tool_calls", None) is not None]
+    assert len(tool_call_chunks) == 2
+    assert tool_call_chunks[0].choices[0].delta.tool_calls[0].function.name == "do_action"
+
+    built = litellm.stream_chunk_builder(chunks=chunks)
+    assert built.choices[0].message.tool_calls[0].function.name == "do_action"
+    assert json.loads(built.choices[0].message.tool_calls[0].function.arguments) == {"action": "run"}