diff --git a/src/llamafactory/data/template.py b/src/llamafactory/data/template.py
index 89b70d1143..dec084cf13 100644
--- a/src/llamafactory/data/template.py
+++ b/src/llamafactory/data/template.py
@@ -57,6 +57,13 @@ class Template:
     preserve_thinking: bool
     mm_plugin: "BasePlugin"
 
+    def _format_system_content(self, system: str, tool_text: str) -> str:
+        if tool_text and self.format_tools.tool_format == "qwen3_5":
+            tool_text = tool_text.lstrip("\n")
+            return tool_text + ("\n\n" + system if system else "")
+
+        return system + tool_text
+
     def encode_oneturn(
         self,
         tokenizer: "PreTrainedTokenizer",
@@ -150,7 +157,7 @@ def _encode(
                 elements += self.format_prefix.apply()
                 if system or tools:
                     tool_text = self.format_tools.apply(content=tools)[0] if tools else ""
-                    elements += self.format_system.apply(content=(system + tool_text))
+                    elements += self.format_system.apply(content=self._format_system_content(system, tool_text))
 
             if message["role"] == Role.USER:
                 elements += self.format_user.apply(content=message["content"], idx=str(i // 2))
diff --git a/tests/data/test_template.py b/tests/data/test_template.py
index ddd7b17da8..db9d038998 100644
--- a/tests/data/test_template.py
+++ b/tests/data/test_template.py
@@ -349,6 +349,27 @@ def test_qwen3_template(cot_messages: bool):
     _check_template("Qwen/Qwen3-8B", "qwen3", prompt_str, answer_str, messages=messages)
 
 
+@pytest.mark.runs_on(["cpu", "mps"])
+def test_qwen35_tools_precede_system_content():
+    tokenizer = AutoTokenizer.from_pretrained(TINY_LLAMA3)
+    template = get_template_and_fix_tokenizer(tokenizer, DataArguments(template="qwen3_5_nothink"))
+    tools = (
+        '[{"type":"function","function":{"name":"lookup_quote","description":"Quote lookup.",'
+        '"parameters":{"type":"object","properties":{},"required":[]}}}]'
+    )
+    prompt_ids, _ = template.encode_oneturn(
+        tokenizer,
+        [
+            {"role": "user", "content": "Check the quote."},
+            {"role": "assistant", "content": "Done."},
+        ],
+        system="You are a market data assistant.",
+        tools=tools,
+    )
+    prompt_str = tokenizer.decode(prompt_ids)
+    assert prompt_str.index("# Tools") < prompt_str.index("You are a market data assistant.")
+
+
 @pytest.mark.runs_on(["cpu", "mps"])
 def test_parse_llama3_template():
     tokenizer = AutoTokenizer.from_pretrained(TINY_LLAMA3)