diff --git a/scripts/autotune_helion_kernels.py b/scripts/autotune_helion_kernels.py
new file mode 100644
index 000000000..755ba3115
--- /dev/null
+++ b/scripts/autotune_helion_kernels.py
@@ -0,0 +1,430 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""
+Autotune registered Helion kernels for optimal configurations.
+
+Usage:
+    # Autotune all registered kernels
+    python scripts/autotune_helion_kernels.py
+
+    # Autotune specific kernel
+    python scripts/autotune_helion_kernels.py --kernels silu_mul_fp8
+
+    # Autotune multiple kernels
+    python scripts/autotune_helion_kernels.py --kernels silu_mul_fp8 rms_norm_fp8
+
+    # Force re-autotuning
+    python scripts/autotune_helion_kernels.py --force
+
+    # List available kernels
+    python scripts/autotune_helion_kernels.py --list
+"""
+
+import argparse
+import sys
+import time
+from dataclasses import dataclass
+
+import torch
+
+try:
+    import helion
+
+    from vllm.kernels.helion import (
+        ConfigManager,
+        get_kernel_by_name,
+        get_registered_kernels,
+    )
+    from vllm.kernels.helion.utils import get_canonical_gpu_name
+    from vllm.logger import init_logger
+    from vllm.utils.import_utils import has_helion
+except ImportError as e:
+    print(f"Error importing vLLM: {e}")
+    print("Please ensure vLLM is installed and in your Python path")
+    sys.exit(1)
+
+logger = init_logger("vllm.scripts.autotune_helion_kernels")
+
+
+@dataclass
+class AutotuneResult:
+    status: str  # "success" | "partial" | "error" | "skipped"
+    successful: int
+    failed: int
+    configs: dict[str, "helion.Config"]
+    message: str = ""
+
+
+def list_kernels() -> None:
+    kernels = get_registered_kernels()
+
+    if not kernels:
+        print("No Helion kernels found in registry.")
+        return
+
+    print("Available Helion kernels:")
+    print("=" * 50)
+
+    for name in sorted(kernels.keys()):
+        print(f"  {name}")
+
+    print(f"\nTotal: {len(kernels)} kernels")
+
+
+def check_requirements() -> bool:
+    if not torch.cuda.is_available():
+        logger.error("CUDA is not available. Helion autotuning requires GPU.")
+        return False
+
+    if not has_helion():
+        logger.error("Helion is not installed. Please install Helion package.")
+        return False
+
+    return True
+
+
+def autotune_kernel(
+    kernel_name: str,
+    platform: str,
+    config_manager: ConfigManager,
+    force: bool = False,
+    autotune_effort: str = "quick",
+) -> AutotuneResult:
+    logger.debug(
+        "Starting autotune for kernel '%s' with effort='%s'",
+        kernel_name,
+        autotune_effort,
+    )
+    kernel_wrapper = get_kernel_by_name(kernel_name)
+    if kernel_wrapper is None:
+        error_msg = f"Kernel '{kernel_name}' not found in registry"
+        logger.error(error_msg)
+        return AutotuneResult(
+            status="error",
+            message=error_msg,
+            successful=0,
+            failed=0,
+            configs={},
+        )
+
+    try:
+        inputs_dict = kernel_wrapper.get_inputs()
+    except NotImplementedError:
+        error_msg = f"Kernel '{kernel_name}' has no input generator registered"
+        logger.error(error_msg)
+        return AutotuneResult(
+            status="error",
+            message=error_msg,
+            successful=0,
+            failed=0,
+            configs={},
+        )
+
+    try:
+        logger.info(
+            "Autotuning kernel '%s' for platform '%s' with %d configs",
+            kernel_name,
+            platform,
+            len(inputs_dict),
+        )
+
+        configs_to_autotune = {}
+        if not force:
+            existing_configs = config_manager.get_platform_configs(
+                kernel_name, platform
+            )
+            for config_key, inputs in inputs_dict.items():
+                if config_key in existing_configs:
+                    logger.debug(
+                        "Config '%s' already exists for platform '%s', skipping",
+                        config_key,
+                        platform,
+                    )
+                else:
+                    configs_to_autotune[config_key] = inputs
+        else:
+            logger.debug("Force mode enabled, will re-autotune all configs")
+            configs_to_autotune = inputs_dict
+
+        if not configs_to_autotune:
+            logger.info(
+                "All configs already exist for kernel '%s' on platform '%s'. "
+                "Use --force to re-autotune.",
+                kernel_name,
+                platform,
+            )
+            return AutotuneResult(
+                status="skipped",
+                message="All configs already exist",
+                successful=0,
+                failed=0,
+                configs={},
+            )
+
+        total_start_time = time.time()
+        autotuned_configs = {}
+        failed_configs = []
+
+        for config_key, inputs in configs_to_autotune.items():
+            logger.info("Autotuning config: %s", config_key)
+            logger.debug(
+                "Input shapes: %s",
+                [getattr(inp, "shape", type(inp).__name__) for inp in inputs],
+            )
+
+            try:
+                config_start_time = time.time()
+                config = kernel_wrapper.run_autotune(inputs, autotune_effort)
+                config_duration = time.time() - config_start_time
+
+                # Save immediately for checkpointing
+                config_manager.save_configs(kernel_name, platform, {config_key: config})
+
+                autotuned_configs[config_key] = config
+                logger.debug("Config details: %s", config)
+
+                logger.info(
+                    "✓ Autotuned and saved config '%s' (%.2fs)",
+                    config_key,
+                    config_duration,
+                )
+
+            except (RuntimeError, ValueError, OSError) as e:
+                logger.exception(
+                    "Failed to autotune config '%s': %s",
+                    config_key,
+                    e,
+                )
+                failed_configs.append(config_key)
+
+        total_duration = time.time() - total_start_time
+        successful = len(autotuned_configs)
+        failed = len(failed_configs)
+
+        logger.info(
+            "Completed autotuning for kernel '%s': %d successful, %d failed (%.2fs)",
+            kernel_name,
+            successful,
+            failed,
+            total_duration,
+        )
+
+        status = "success" if failed == 0 else "partial"
+        return AutotuneResult(
+            status=status,
+            successful=successful,
+            failed=failed,
+            configs=autotuned_configs,
+        )
+
+    except (KeyError, RuntimeError, ValueError, OSError) as e:
+        error_msg = f"Unexpected error: {e}"
+        logger.exception("Failed to autotune kernel '%s': %s", kernel_name, e)
+        return AutotuneResult(
+            status="error",
+            message=error_msg,
+            successful=0,
+            failed=0,
+            configs={},
+        )
+
+
+def summarize_results(results: dict[str, AutotuneResult]) -> bool:
+    logger.info("=" * 50)
+    logger.info("Autotuning Results Summary")
+    logger.info("=" * 50)
+
+    total_successful = 0
+    total_failed = 0
+    success_kernels = []
+    partial_kernels = []
+    error_kernels = []
+    skipped_kernels = []
+
+    for kernel_name, result in results.items():
+        total_successful += result.successful
+        total_failed += result.failed
+
+        if result.status == "success":
+            success_kernels.append(f"{kernel_name} ({result.successful} configs)")
+            logger.info("✓ %s: %d configs successful", kernel_name, result.successful)
+        elif result.status == "partial":
+            partial_kernels.append(
+                f"{kernel_name} ({result.successful} ok, {result.failed} failed)"
+            )
+            logger.warning(
+                "⚠ %s: %d successful, %d failed",
+                kernel_name,
+                result.successful,
+                result.failed,
+            )
+        elif result.status == "error":
+            error_kernels.append(f"{kernel_name}: {result.message or 'Unknown error'}")
+            logger.error("✗ %s: %s", kernel_name, result.message or "Unknown error")
+        elif result.status == "skipped":
+            skipped_kernels.append(f"{kernel_name}: {result.message or 'Skipped'}")
+            logger.info("- %s: %s", kernel_name, result.message or "Skipped")
+
+    logger.info("=" * 50)
+    logger.info(
+        "Summary: %d total configs (%d successful, %d failed)",
+        total_successful + total_failed,
+        total_successful,
+        total_failed,
+    )
+    logger.info(
+        "Kernels: %d success, %d partial, %d error, %d skipped",
+        len(success_kernels),
+        len(partial_kernels),
+        len(error_kernels),
+        len(skipped_kernels),
+    )
+
+    has_failures = bool(error_kernels or partial_kernels)
+
+    if not has_failures:
+        if total_successful > 0:
+            logger.info("All configs autotuned successfully!")
+        else:
+            logger.info("No new configs were generated (all may already exist)")
+
+    return not has_failures
+
+
+def get_kernels_to_autotune(requested_kernels: list[str] | None) -> list[str]:
+    all_kernels = get_registered_kernels()
+    if not all_kernels:
+        logger.error("No Helion kernels found in registry")
+        sys.exit(1)
+
+    if not requested_kernels:
+        return list(all_kernels.keys())
+
+    if len(requested_kernels) != len(set(requested_kernels)):
+        duplicates = [
+            k for k in set(requested_kernels) if requested_kernels.count(k) > 1
+        ]
+        logger.error("Duplicate kernel names in --kernels flag: %s", duplicates)
+        sys.exit(1)
+
+    kernels_to_autotune = []
+    missing_kernels = []
+
+    for kernel_name in requested_kernels:
+        if kernel_name in all_kernels:
+            kernels_to_autotune.append(kernel_name)
+        else:
+            missing_kernels.append(kernel_name)
+
+    if missing_kernels:
+        logger.error("Kernel(s) not found: %s", missing_kernels)
+        logger.error("Available kernels: %s", list(all_kernels.keys()))
+        sys.exit(1)
+
+    return kernels_to_autotune
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Autotune Helion kernels",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=__doc__.split("Usage:")[1] if "Usage:" in __doc__ else "",
+    )
+
+    parser.add_argument(
+        "--kernels",
+        nargs="+",
+        help="Kernel(s) to autotune (default: all kernels)",
+    )
+
+    parser.add_argument(
+        "--config-dir",
+        type=str,
+        help="Config directory for config files (default: vLLM helion configs dir)",
+    )
+
+    parser.add_argument(
+        "--list",
+        action="store_true",
+        help="List available Helion kernels and exit",
+    )
+
+    parser.add_argument(
+        "--force",
+        action="store_true",
+        help=(
+            "Force re-autotuning even if configs already exist for the "
+            "platform and config keys"
+        ),
+    )
+
+    parser.add_argument(
+        "--autotune-effort",
+        type=str,
+        default="quick",
+        help=(
+            "Helion autotune effort level: 'quick' (smaller search) or "
+            "'full' (full search budget) (default: quick)"
+        ),
+    )
+
+    parser.add_argument(
+        "--verbose",
+        action="store_true",
+        help="Enable verbose logging",
+    )
+
+    args = parser.parse_args()
+
+    import logging
+
+    if args.verbose:
+        logging.getLogger("vllm").setLevel(logging.DEBUG)
+        logger.debug("Verbose mode enabled")
+        logger.debug("Arguments: %s", vars(args))
+    else:
+        logging.getLogger("vllm").setLevel(logging.INFO)
+
+    if args.list:
+        list_kernels()
+        return
+
+    if not check_requirements():
+        sys.exit(1)
+
+    platform = get_canonical_gpu_name()
+    logger.info("Detected GPU platform: %s", platform)
+
+    config_manager = (
+        ConfigManager(args.config_dir) if args.config_dir else ConfigManager()
+    )
+
+    try:
+        config_manager.ensure_base_dir_writable()
+    except OSError as e:
+        logger.error("Failed to access config directory: %s", e)
+        sys.exit(1)
+
+    kernels_to_autotune = get_kernels_to_autotune(args.kernels)
+
+    logger.info(
+        "Will autotune %d kernel(s) for platform '%s': %s",
+        len(kernels_to_autotune),
+        platform,
+        kernels_to_autotune,
+    )
+
+    results = {}
+    for kernel_name in kernels_to_autotune:
+        result = autotune_kernel(
+            kernel_name, platform, config_manager, args.force, args.autotune_effort
+        )
+        results[kernel_name] = result
+
+    success = summarize_results(results)
+    sys.exit(0 if success else 1)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/vllm/kernels/helion/config_manager.py b/vllm/kernels/helion/config_manager.py
index 63560761e..3c53106ce 100644
--- a/vllm/kernels/helion/config_manager.py
+++ b/vllm/kernels/helion/config_manager.py
@@ -131,6 +131,27 @@ class ConfigSet:
 
         return config_set
 
+    def set_config(
+        self, platform: str, config_key: str, config: "helion.Config"
+    ) -> None:
+        platform = platform.lower()
+        if platform not in self._configs:
+            self._configs[platform] = {}
+        self._configs[platform][config_key] = config
+        logger.debug(
+            "Set config for kernel '%s': platform='%s', key='%s'",
+            self._kernel_name,
+            platform,
+            config_key,
+        )
+
+    def has_config(self, platform: str, config_key: str) -> bool:
+        platform = platform.lower()
+        platform_dict = self._configs.get(platform)
+        if platform_dict is None:
+            return False
+        return config_key in platform_dict
+
 
 class ConfigManager:
     """File-level configuration management for Helion kernels (global singleton)."""
@@ -142,7 +163,6 @@ class ConfigManager:
         resolved_base_dir = cls._resolve_base_dir(base_dir)
 
         if cls._instance is not None:
-            # Instance already exists - check for base_dir mismatch
             if cls._instance_base_dir != resolved_base_dir:
                 raise ValueError(
                     f"ConfigManager singleton already exists with base_dir "
@@ -151,14 +171,12 @@ class ConfigManager:
                 )
             return cls._instance
 
-        # Create new instance
         instance = super().__new__(cls)
         cls._instance = instance
         cls._instance_base_dir = resolved_base_dir
         return instance
 
     def __init__(self, base_dir: str | Path | None = None):
-        # Only initialize if not already initialized
         if hasattr(self, "_base_dir"):
             return
 
@@ -193,6 +211,17 @@ class ConfigManager:
         self._base_dir.mkdir(parents=True, exist_ok=True)
         return self._base_dir
 
+    def ensure_base_dir_writable(self) -> None:
+        self.ensure_base_dir_exists()
+        test_file = self._base_dir / ".write_test"
+        try:
+            test_file.write_text("test")
+            test_file.unlink()
+        except OSError as e:
+            raise OSError(
+                f"Config directory '{self._base_dir}' is not writable: {e}"
+            ) from e
+
     def load_config_set(self, kernel_name: str) -> ConfigSet:
         config_path = self.get_config_file_path(kernel_name)
         if not config_path.exists():
@@ -226,3 +255,19 @@ class ConfigManager:
 
         logger.info("Saved config to: %s", config_path)
         return config_path
+
+    def save_configs(
+        self,
+        kernel_name: str,
+        platform: str,
+        configs: dict[str, "helion.Config"],
+    ) -> Path:
+        """Save configs for a kernel/platform, merging with existing."""
+        config_set = self.load_config_set(kernel_name)
+        for config_key, config in configs.items():
+            config_set.set_config(platform, config_key, config)
+        return self.save_config_set(config_set)
+
+    def config_exists(self, kernel_name: str, platform: str, config_key: str) -> bool:
+        config_set = self.load_config_set(kernel_name)
+        return config_set.has_config(platform, config_key)
diff --git a/vllm/kernels/helion/register.py b/vllm/kernels/helion/register.py
index b90110724..3114631dd 100644
--- a/vllm/kernels/helion/register.py
+++ b/vllm/kernels/helion/register.py
@@ -65,7 +65,6 @@ vllm_helion_lib = Library("vllm_helion", "FRAGMENT")  # noqa
 def validate_helion_settings(
     helion_settings: "helion.Settings | None", op_name: str
 ) -> None:
-    """Validate that helion_settings doesn't contain conflicting options."""
     if helion_settings is None:
         return
 
@@ -93,6 +92,26 @@ def validate_helion_settings(
         )
 
 
+def create_helion_decorated_kernel(
+    raw_kernel_func: Callable,
+    helion_settings: "helion.Settings | None" = None,
+    extra_kwargs: dict[str, Any] | None = None,
+) -> Any:
+    kernel_kwargs: dict[str, Any] = {}
+    if helion_settings:
+        kernel_kwargs.update(helion_settings.to_dict())
+
+    # Set static_shapes=False by default if user didn't explicitly set it
+    # This is needed for dynamic batch sizes and sequence lengths in vLLM
+    if kernel_kwargs.get("static_shapes") is not True:
+        kernel_kwargs["static_shapes"] = False
+
+    if extra_kwargs:
+        kernel_kwargs.update(extra_kwargs)
+
+    return helion.kernel(**kernel_kwargs)(raw_kernel_func)
+
+
 class PresetConfigSearch(BaseAutotuner):
     """Custom autotuner that uses a preset config selector instead of autotuning."""
 
@@ -198,26 +217,19 @@ class ConfiguredHelionKernel:
         key_computer = self._create_key_computer()
         config_selector = self._create_config_selector(key_computer)
 
-        kernel_kwargs = {}
-        if self.helion_settings:
-            kernel_kwargs.update(self.helion_settings.to_dict())
-
-        # Set static_shapes=False by default if user didn't explicitly set it to True
-        # This is needed for dynamic batch sizes and sequence lengths in vLLM
-        if kernel_kwargs.get("static_shapes") is not True:
-            kernel_kwargs["static_shapes"] = False
-
-        kernel_kwargs["autotuner_fn"] = lambda _, args: PresetConfigSearch(
-            args, config_selector
-        )
-        kernel_kwargs["key"] = key_computer
+        extra_kwargs = {
+            "autotuner_fn": lambda _, args: PresetConfigSearch(args, config_selector),
+            "key": key_computer,
+        }
 
         logger.debug(
             "Creating decorated kernel %s with custom autotuner on platform %s",
             self.op_name,
             self.platform,
         )
-        return helion.kernel(**kernel_kwargs)(self.raw_kernel_func)
+        return create_helion_decorated_kernel(
+            self.raw_kernel_func, self.helion_settings, extra_kwargs
+        )
 
 
 class HelionKernelWrapper:
@@ -240,6 +252,7 @@ class HelionKernelWrapper:
         self._config_picker: (
             Callable[[tuple[Any, ...], list[str]], str | None] | None
         ) = None
+        self._input_generator: Callable[[], dict[str, tuple[Any, ...]]] | None = None
 
     def __call__(self, *args, **kwargs):
         configured_op = self.get_configured_op()
@@ -251,6 +264,51 @@ class HelionKernelWrapper:
         self._config_picker = picker_func
         return picker_func
 
+    def register_input_generator(
+        self, generator_func: Callable[[], dict[str, tuple[Any, ...]]]
+    ) -> Callable[[], dict[str, tuple[Any, ...]]]:
+        """
+        Register a function to generate inputs for autotuning and benchmarking.
+
+        Args:
+            generator_func: Function that returns dict[str, tuple] where:
+                - key: Configuration identifier (e.g., "4096", "hidden_4096")
+                - value: Tuple of arguments to pass to the kernel
+
+        Returns:
+            The registered function (for decorator usage)
+
+        Example:
+            @kernel_wrapper.register_input_generator
+            def generate_inputs():
+                return {
+                    "4096": (torch.randn(4096, device="cuda"), 0.5),
+                    "8192": (torch.randn(8192, device="cuda"), 0.5),
+                }
+        """
+        self._input_generator = generator_func
+        return generator_func
+
+    def get_inputs(self) -> dict[str, tuple[Any, ...]]:
+        if self._input_generator is None:
+            raise NotImplementedError(
+                f"No input generator registered for kernel '{self.op_name}'. "
+                f"Use @{self.op_name}.register_input_generator to register one."
+            )
+        return self._input_generator()
+
+    def run_autotune(
+        self,
+        inputs: tuple[Any, ...],
+        autotune_effort: str = "quick",
+    ) -> Config:
+        """Run autotuning for a single input configuration."""
+        extra_kwargs = {"autotune_effort": autotune_effort}
+        autotune_kernel = create_helion_decorated_kernel(
+            self.raw_kernel_func, self.helion_settings, extra_kwargs
+        )
+        return autotune_kernel.autotune(inputs)
+
     def get_configured_op(self) -> Any:
         assert self._config_picker is not None, (
             f"No config picker registered for kernel '{self.op_name}'. "