diff --git a/api/core/model_runtime/model_providers/__base/large_language_model.py b/api/core/model_runtime/model_providers/__base/large_language_model.py
index bbbdec61d1..c32ab0879e 100644
--- a/api/core/model_runtime/model_providers/__base/large_language_model.py
+++ b/api/core/model_runtime/model_providers/__base/large_language_model.py
@@ -83,19 +83,21 @@ def _merge_tool_call_delta(
         tool_call.function.arguments += delta.function.arguments
 
 
-def _build_llm_result_from_first_chunk(
+def _build_llm_result_from_chunks(
     model: str,
     prompt_messages: Sequence[PromptMessage],
     chunks: Iterator[LLMResultChunk],
 ) -> LLMResult:
     """
-    Build a single `LLMResult` from the first returned chunk.
+    Build a single `LLMResult` by accumulating all returned chunks.
 
-    This is used for `stream=False` because the plugin side may still implement the response via a chunked stream.
+    Some models only support streaming output (e.g. Qwen3 open-source edition)
+    and the plugin side may still implement the response via a chunked stream,
+    so all chunks must be consumed and concatenated into a single ``LLMResult``.
 
-    Note:
-        This function always drains the `chunks` iterator after reading the first chunk to ensure any underlying
-        streaming resources are released (e.g., HTTP connections owned by the plugin runtime).
+    The ``usage`` is taken from the last chunk that carries it, which is the
+    typical convention for streaming responses (the final chunk contains the
+    aggregated token counts).
     """
     content = ""
     content_list: list[PromptMessageContentUnionTypes] = []
@@ -104,24 +106,27 @@ def _build_llm_result_from_first_chunk(
     tools_calls: list[AssistantPromptMessage.ToolCall] = []
 
     try:
-        first_chunk = next(chunks, None)
-        if first_chunk is not None:
-            if isinstance(first_chunk.delta.message.content, str):
-                content += first_chunk.delta.message.content
-            elif isinstance(first_chunk.delta.message.content, list):
-                content_list.extend(first_chunk.delta.message.content)
+        for chunk in chunks:
+            if isinstance(chunk.delta.message.content, str):
+                content += chunk.delta.message.content
+            elif isinstance(chunk.delta.message.content, list):
+                content_list.extend(chunk.delta.message.content)
 
-            if first_chunk.delta.message.tool_calls:
-                _increase_tool_call(first_chunk.delta.message.tool_calls, tools_calls)
+            if chunk.delta.message.tool_calls:
+                _increase_tool_call(chunk.delta.message.tool_calls, tools_calls)
 
-            usage = first_chunk.delta.usage or LLMUsage.empty_usage()
-            system_fingerprint = first_chunk.system_fingerprint
+            if chunk.delta.usage:
+                usage = chunk.delta.usage
+            if chunk.system_fingerprint:
+                system_fingerprint = chunk.system_fingerprint
+    except Exception:
+        logger.exception("Error while consuming non-stream plugin chunk iterator.")
+        raise
     finally:
-        try:
-            for _ in chunks:
-                pass
-        except Exception:
-            logger.debug("Failed to drain non-stream plugin chunk iterator.", exc_info=True)
+        # Drain any remaining chunks to release underlying streaming resources (e.g. HTTP connections).
+        close = getattr(chunks, "close", None)
+        if callable(close):
+            close()
 
     return LLMResult(
         model=model,
@@ -174,7 +179,7 @@ def _normalize_non_stream_plugin_result(
 ) -> LLMResult:
     if isinstance(result, LLMResult):
         return result
-    return _build_llm_result_from_first_chunk(model=model, prompt_messages=prompt_messages, chunks=result)
+    return _build_llm_result_from_chunks(model=model, prompt_messages=prompt_messages, chunks=result)
 
 
 def _increase_tool_call(
diff --git a/api/tests/unit_tests/core/model_runtime/__base/test_large_language_model_non_stream_parsing.py b/api/tests/unit_tests/core/model_runtime/__base/test_large_language_model_non_stream_parsing.py
index cfdeef6a8d..09d527cb12 100644
--- a/api/tests/unit_tests/core/model_runtime/__base/test_large_language_model_non_stream_parsing.py
+++ b/api/tests/unit_tests/core/model_runtime/__base/test_large_language_model_non_stream_parsing.py
@@ -103,16 +103,16 @@ def test__normalize_non_stream_plugin_result__empty_iterator_defaults():
     assert result.system_fingerprint is None
 
 
-def test__normalize_non_stream_plugin_result__closes_chunk_iterator():
+def test__normalize_non_stream_plugin_result__accumulates_all_chunks():
+    """All chunks are accumulated from the iterator."""
     prompt_messages = [UserPromptMessage(content="hi")]
 
-    chunk = _make_chunk(content="hello", usage=LLMUsage.empty_usage())
     closed: list[bool] = []
 
     def _chunk_iter():
         try:
-            yield chunk
-            yield _make_chunk(content="ignored", usage=LLMUsage.empty_usage())
+            yield _make_chunk(content="hello", usage=LLMUsage.empty_usage())
+            yield _make_chunk(content=" world", usage=LLMUsage.empty_usage())
         finally:
             closed.append(True)
 
@@ -122,5 +122,5 @@ def test__normalize_non_stream_plugin_result__closes_chunk_iterator():
         result=_chunk_iter(),
     )
 
-    assert result.message.content == "hello"
+    assert result.message.content == "hello world"
     assert closed == [True]