diff --git a/tests/entrypoints/openai/chat_completion/test_chat_error.py b/tests/entrypoints/openai/chat_completion/test_chat_error.py
index 582e079215..e099c282f4 100644
--- a/tests/entrypoints/openai/chat_completion/test_chat_error.py
+++ b/tests/entrypoints/openai/chat_completion/test_chat_error.py
@@ -6,9 +6,13 @@ from typing import Any
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
+from pydantic import ValidationError
 
 from vllm.config.multimodal import MultiModalConfig
-from vllm.entrypoints.openai.chat_completion.protocol import ChatCompletionRequest
+from vllm.entrypoints.openai.chat_completion.protocol import (
+    BatchChatCompletionRequest,
+    ChatCompletionRequest,
+)
 from vllm.entrypoints.openai.chat_completion.serving import OpenAIServingChat
 from vllm.entrypoints.openai.engine.protocol import GenerationError
 from vllm.entrypoints.openai.models.protocol import BaseModelPath
@@ -444,3 +448,45 @@ def test_json_schema_response_format_missing_schema():
             messages=[{"role": "user", "content": "hello"}],
             response_format={"type": "json_schema"},
         )
+
+
+@pytest.mark.parametrize("format_value", [None, {}])
+def test_structural_tag_response_format_invalid(format_value):
+    """Malformed structural tags should be rejected during request validation."""
+    with pytest.raises(
+        ValidationError,
+        match="Invalid response_format structural_tag",
+    ):
+        ChatCompletionRequest(
+            model=MODEL_NAME,
+            messages=[{"role": "user", "content": "hello"}],
+            response_format={"type": "structural_tag", "format": format_value},
+        )
+
+
+@pytest.mark.parametrize("format_value", [None, {}])
+def test_batch_structural_tag_response_format_invalid(format_value):
+    """Batch chat should reject malformed structural tags at request parsing."""
+    with pytest.raises(
+        ValidationError,
+        match="Invalid response_format structural_tag",
+    ):
+        BatchChatCompletionRequest(
+            model=MODEL_NAME,
+            messages=[[{"role": "user", "content": "hello"}]],
+            response_format={"type": "structural_tag", "format": format_value},
+        )
+
+
+@pytest.mark.parametrize("structural_tag", ["not json", ""])
+def test_structured_outputs_structural_tag_invalid(structural_tag):
+    """Malformed direct structured_outputs structural tags should be rejected."""
+    with pytest.raises(
+        ValidationError,
+        match="Invalid structured_outputs structural_tag",
+    ):
+        ChatCompletionRequest(
+            model=MODEL_NAME,
+            messages=[{"role": "user", "content": "hello"}],
+            structured_outputs={"structural_tag": structural_tag},
+        )
diff --git a/tests/entrypoints/openai/completion/test_completion_error.py b/tests/entrypoints/openai/completion/test_completion_error.py
index c95e47fa1b..71a70a4d0e 100644
--- a/tests/entrypoints/openai/completion/test_completion_error.py
+++ b/tests/entrypoints/openai/completion/test_completion_error.py
@@ -6,6 +6,7 @@ from typing import Any
 from unittest.mock import AsyncMock, MagicMock
 
 import pytest
+from pydantic import ValidationError
 
 from vllm.config.multimodal import MultiModalConfig
 from vllm.entrypoints.openai.completion.protocol import CompletionRequest
@@ -302,6 +303,36 @@ def test_json_schema_response_format_missing_schema():
         )
 
 
+@pytest.mark.parametrize("format_value", [None, {}])
+def test_structural_tag_response_format_invalid(format_value):
+    """Malformed structural tags should be rejected during request validation."""
+    with pytest.raises(
+        ValidationError,
+        match="Invalid response_format structural_tag",
+    ):
+        CompletionRequest(
+            model=MODEL_NAME,
+            prompt="Test prompt",
+            max_tokens=10,
+            response_format={"type": "structural_tag", "format": format_value},
+        )
+
+
+@pytest.mark.parametrize("structural_tag", ["not json", ""])
+def test_structured_outputs_structural_tag_invalid(structural_tag):
+    """Malformed direct structured_outputs structural tags should be rejected."""
+    with pytest.raises(
+        ValidationError,
+        match="Invalid structured_outputs structural_tag",
+    ):
+        CompletionRequest(
+            model=MODEL_NAME,
+            prompt="Test prompt",
+            max_tokens=10,
+            structured_outputs={"structural_tag": structural_tag},
+        )
+
+
 def test_negative_prompt_token_ids_nested():
     """Negative token IDs in prompt (nested list) should raise validation error."""
     with pytest.raises(Exception, match="greater than or equal to 0"):
diff --git a/tests/tool_parsers/test_mistral_tool_parser.py b/tests/tool_parsers/test_mistral_tool_parser.py
index f6a5c6bfb2..c9582159ab 100644
--- a/tests/tool_parsers/test_mistral_tool_parser.py
+++ b/tests/tool_parsers/test_mistral_tool_parser.py
@@ -1382,7 +1382,20 @@ def test_adjust_request_non_mistral_tokenizer(
     [
         {"regex": r"\d+"},
         {"choice": ["a", "b"]},
-        {"structural_tag": '{"key": "value"}'},
+        {
+            "structural_tag": json.dumps(
+                {
+                    "structures": [
+                        {
+                            "begin": "<tool>",
+                            "schema": {"type": "object"},
+                            "end": "</tool>",
+                        }
+                    ],
+                    "triggers": ["<tool>"],
+                }
+            )
+        },
         {"grammar": "start: 'hello'"},
     ],
     ids=["regex", "choice", "structural_tag", "grammar"],
@@ -1404,7 +1417,18 @@ def test_adjust_request_unsupported_response_format(
 ) -> None:
     request = _make_request(
         response_format=StructuralTagResponseFormat(
-            type="structural_tag", format={"some": "config"}
+            type="structural_tag",
+            format={
+                "type": "triggered_tags",
+                "tags": [
+                    {
+                        "begin": "<tool>",
+                        "content": {"type": "any_text"},
+                        "end": "</tool>",
+                    }
+                ],
+                "triggers": ["<tool>"],
+            },
         ),
     )
     result = mistral_tool_parser.adjust_request(request)
diff --git a/vllm/entrypoints/openai/chat_completion/protocol.py b/vllm/entrypoints/openai/chat_completion/protocol.py
index 0be220fff7..184ace5680 100644
--- a/vllm/entrypoints/openai/chat_completion/protocol.py
+++ b/vllm/entrypoints/openai/chat_completion/protocol.py
@@ -30,6 +30,8 @@ from vllm.entrypoints.openai.engine.protocol import (
     StructuralTagResponseFormat,
     ToolCall,
     UsageInfo,
+    validate_structural_tag_response_format,
+    validate_structured_outputs_structural_tag,
 )
 from vllm.exceptions import VLLMValidationError
 from vllm.logger import init_logger
@@ -671,6 +673,9 @@ class ChatCompletionRequest(OpenAIBaseModel):
                     parameter="response_format",
                 )
 
+        if rf_type == "structural_tag":
+            validate_structural_tag_response_format(response_format)
+
         return data
 
     @model_validator(mode="before")
@@ -754,6 +759,7 @@ class ChatCompletionRequest(OpenAIBaseModel):
                 "You can only either use constraints for structured outputs "
                 "or tools, not both.",
             )
+        validate_structured_outputs_structural_tag(structured_outputs_kwargs)
         return data
 
     @model_validator(mode="before")
@@ -979,6 +985,16 @@ class BatchChatCompletionRequest(OpenAIBaseModel):
                 "Batch chat completions do not support beam search. "
                 "Please set `use_beam_search` to False."
             )
+        response_format = data.get("response_format")
+        rf_type = (
+            response_format.get("type")
+            if isinstance(response_format, dict)
+            else getattr(response_format, "type", None)
+        )
+        if rf_type == "structural_tag":
+            validate_structural_tag_response_format(response_format)
+        if (structured_outputs := data.get("structured_outputs")) is not None:
+            validate_structured_outputs_structural_tag(structured_outputs)
         n = data.get("n", 1)
         if n is not None and n != 1:
             raise ValueError(
diff --git a/vllm/entrypoints/openai/completion/protocol.py b/vllm/entrypoints/openai/completion/protocol.py
index a6c3f9c93d..30a4f20084 100644
--- a/vllm/entrypoints/openai/completion/protocol.py
+++ b/vllm/entrypoints/openai/completion/protocol.py
@@ -18,6 +18,8 @@ from vllm.entrypoints.openai.engine.protocol import (
     StreamOptions,
     StructuralTagResponseFormat,
     UsageInfo,
+    validate_structural_tag_response_format,
+    validate_structured_outputs_structural_tag,
 )
 from vllm.exceptions import VLLMValidationError
 from vllm.logger import init_logger
@@ -370,6 +372,9 @@ class CompletionRequest(OpenAIBaseModel):
                     parameter="response_format",
                 )
 
+        if rf_type == "structural_tag":
+            validate_structural_tag_response_format(response_format)
+
         return data
 
     @model_validator(mode="before")
@@ -397,6 +402,7 @@ class CompletionRequest(OpenAIBaseModel):
                 "outputs ('json', 'regex' or 'choice').",
                 parameter="structured_outputs",
             )
+        validate_structured_outputs_structural_tag(structured_outputs_kwargs)
         return data
 
     @model_validator(mode="before")
diff --git a/vllm/entrypoints/openai/engine/protocol.py b/vllm/entrypoints/openai/engine/protocol.py
index 890af0300e..434888df9e 100644
--- a/vllm/entrypoints/openai/engine/protocol.py
+++ b/vllm/entrypoints/openai/engine/protocol.py
@@ -17,6 +17,7 @@ from pydantic import (
 )
 
 from vllm.entrypoints.chat_utils import make_tool_call_id
+from vllm.exceptions import VLLMValidationError
 from vllm.logger import init_logger
 from vllm.utils import random_uuid
 from vllm.utils.import_utils import resolve_obj_by_qualname
@@ -158,6 +159,80 @@ AnyResponseFormat: TypeAlias = (
 )
 
 
+def validate_structural_tag_response_format(
+    response_format: AnyStructuralTagResponseFormat | dict[str, Any],
+) -> None:
+    """Validate structural tags before they are sent to the engine.
+
+    Engine-side validation reports malformed structural tags as generation
+    failures. OpenAI request parsing should classify them as bad requests.
+    """
+    import json
+
+    from pydantic import TypeAdapter, ValidationError
+
+    if isinstance(response_format, dict):
+        try:
+            response_format = TypeAdapter(
+                AnyStructuralTagResponseFormat
+            ).validate_python(response_format)
+        except ValidationError as exc:
+            raise VLLMValidationError(
+                "Invalid response_format structural_tag specification.",
+                parameter="response_format",
+            ) from exc
+
+    try:
+        payload = json.dumps(response_format.model_dump(by_alias=True))
+        validate_structural_tag_payload(payload, parameter="response_format")
+    except (TypeError, ValueError) as exc:
+        raise VLLMValidationError(
+            "Invalid response_format structural_tag specification.",
+            parameter="response_format",
+        ) from exc
+
+
+def validate_structural_tag_payload(payload: Any, *, parameter: str) -> None:
+    from vllm.sampling_params import SamplingParams, StructuredOutputsParams
+    from vllm.v1.structured_output.backend_xgrammar import validate_xgrammar_grammar
+
+    if isinstance(payload, str) and not payload:
+        raise VLLMValidationError(
+            f"Invalid {parameter} structural_tag specification.",
+            parameter=parameter,
+        )
+
+    try:
+        validate_xgrammar_grammar(
+            SamplingParams(
+                structured_outputs=StructuredOutputsParams(structural_tag=payload)
+            )
+        )
+    except (TypeError, ValueError) as exc:
+        raise VLLMValidationError(
+            f"Invalid {parameter} structural_tag specification.",
+            parameter=parameter,
+        ) from exc
+
+
+def validate_structured_outputs_structural_tag(
+    structured_outputs: Any,
+) -> None:
+    from vllm.sampling_params import StructuredOutputsParams
+
+    if isinstance(structured_outputs, StructuredOutputsParams):
+        structural_tag = structured_outputs.structural_tag
+    elif isinstance(structured_outputs, dict):
+        structural_tag = structured_outputs.get("structural_tag")
+    else:
+        return
+    if structural_tag is not None:
+        validate_structural_tag_payload(
+            structural_tag,
+            parameter="structured_outputs",
+        )
+
+
 class StreamOptions(OpenAIBaseModel):
     include_usage: bool | None = False
     continuous_usage_stats: bool | None = False