diff --git a/tests/kernels/quantization/test_fp8_min_max_helper.py b/tests/kernels/quantization/test_fp8_min_max_helper.py
new file mode 100644
index 0000000000000..b19637b3adef5
--- /dev/null
+++ b/tests/kernels/quantization/test_fp8_min_max_helper.py
@@ -0,0 +1,93 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""
+Unit tests for the get_fp8_min_max() helper function.
+
+These tests verify the FP8 min/max value logic for both standard
+and fnuz (ROCm MI300) dtype handling.
+"""
+
+from unittest.mock import patch
+
+import pytest
+import torch
+
+
+class TestGetFp8MinMax:
+    """Test cases for get_fp8_min_max() function."""
+
+    def test_standard_fp8_dtype(self):
+        """Test that standard FP8 dtype uses PyTorch's finfo values."""
+        from vllm.model_executor.layers.quantization.utils.quant_utils import (
+            get_fp8_min_max,
+        )
+
+        # For standard float8_e4m3fn, should return finfo values
+        fp8_min, fp8_max = get_fp8_min_max(torch.float8_e4m3fn)
+        finfo = torch.finfo(torch.float8_e4m3fn)
+
+        # Standard FP8 max is 448.0 for e4m3fn
+        assert fp8_max == finfo.max, f"Expected finfo.max={finfo.max}, got {fp8_max}"
+        assert fp8_min == finfo.min, f"Expected finfo.min={finfo.min}, got {fp8_min}"
+
+    @patch("vllm.model_executor.layers.quantization.utils.quant_utils.current_platform")
+    def test_fnuz_fp8_dtype_on_fnuz_platform(self, mock_platform):
+        """Test that fnuz dtype on fnuz platform returns 224.0."""
+        mock_platform.is_fp8_fnuz.return_value = True
+        mock_platform.fp8_dtype.return_value = torch.float8_e4m3fnuz
+
+        # Re-import to use mocked platform
+        from importlib import reload
+
+        import vllm.model_executor.layers.quantization.utils.quant_utils as qu
+
+        reload(qu)
+
+        fp8_min, fp8_max = qu.get_fp8_min_max(torch.float8_e4m3fnuz)
+
+        # fnuz on ROCm MI300 should return 224.0, not 240.0
+        assert fp8_max == 224.0, (
+            f"Expected 224.0 for fnuz on fnuz platform, got {fp8_max}"
+        )
+        assert fp8_min == -224.0, (
+            f"Expected -224.0 for fnuz on fnuz platform, got {fp8_min}"
+        )
+
+    @patch("vllm.model_executor.layers.quantization.utils.quant_utils.current_platform")
+    def test_standard_dtype_on_fnuz_platform(self, mock_platform):
+        """Test that standard dtype on fnuz platform uses finfo values."""
+        mock_platform.is_fp8_fnuz.return_value = True
+
+        from vllm.model_executor.layers.quantization.utils.quant_utils import (
+            get_fp8_min_max,
+        )
+
+        # Standard e4m3fn dtype should use finfo even on fnuz platform
+        fp8_min, fp8_max = get_fp8_min_max(torch.float8_e4m3fn)
+        finfo = torch.finfo(torch.float8_e4m3fn)
+
+        assert fp8_max == finfo.max, (
+            f"Standard dtype should use finfo.max={finfo.max}, got {fp8_max}"
+        )
+
+    @patch("vllm.model_executor.layers.quantization.utils.quant_utils.current_platform")
+    def test_fnuz_dtype_on_non_fnuz_platform(self, mock_platform):
+        """Test that fnuz dtype on non-fnuz platform uses finfo values."""
+        mock_platform.is_fp8_fnuz.return_value = False
+
+        from vllm.model_executor.layers.quantization.utils.quant_utils import (
+            get_fp8_min_max,
+        )
+
+        # fnuz dtype on non-fnuz platform should use finfo
+        fp8_min, fp8_max = get_fp8_min_max(torch.float8_e4m3fnuz)
+        finfo = torch.finfo(torch.float8_e4m3fnuz)
+
+        # Should be 240.0, not 224.0 (non-fnuz platform)
+        assert fp8_max == finfo.max, (
+            f"Non-fnuz platform should use finfo.max={finfo.max}, got {fp8_max}"
+        )
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])