diff --git a/litellm/llms/vertex_ai/videos/transformation.py b/litellm/llms/vertex_ai/videos/transformation.py
index eb368245eb7..b925f82c886 100644
--- a/litellm/llms/vertex_ai/videos/transformation.py
+++ b/litellm/llms/vertex_ai/videos/transformation.py
@@ -7,6 +7,8 @@ Based on: https://docs.cloud.google.com/vertex-ai/generative-ai/docs/model-refer
 
 import base64
 import time
+from collections.abc import Mapping
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, ClassVar, Final, cast
 
 import httpx
@@ -92,18 +94,22 @@ class VertexAIVideoConfig(BaseVideoConfig, VertexBase):
     3. Extract video data (base64) from response
     """
 
-    _OPENAI_VIDEO_SIZE_TO_ASPECT_RATIO: ClassVar[dict[str, str]] = {
-        "1280x720": "16:9",
-        "1920x1080": "16:9",
-        "720x1280": "9:16",
-        "1080x1920": "9:16",
-    }
-    _OPENAI_VIDEO_SIZE_TO_RESOLUTION: ClassVar[dict[str, str]] = {
-        "1280x720": "720p",
-        "1920x1080": "1080p",
-        "720x1280": "720p",
-        "1080x1920": "1080p",
-    }
+    _OPENAI_VIDEO_SIZE_TO_ASPECT_RATIO: ClassVar[Mapping[str, str]] = MappingProxyType(
+        {
+            "1280x720": "16:9",
+            "1920x1080": "16:9",
+            "720x1280": "9:16",
+            "1080x1920": "9:16",
+        }
+    )
+    _OPENAI_VIDEO_SIZE_TO_RESOLUTION: ClassVar[Mapping[str, str]] = MappingProxyType(
+        {
+            "1280x720": "720p",
+            "1920x1080": "1080p",
+            "720x1280": "720p",
+            "1080x1920": "1080p",
+        }
+    )
 
     def __init__(self):
         BaseVideoConfig.__init__(self)
@@ -213,9 +219,9 @@ class VertexAIVideoConfig(BaseVideoConfig, VertexBase):
 
     @staticmethod
     def _supports_resolution_inference(model: str) -> bool:
-        model_key = model if model.startswith("vertex_ai/") else f"vertex_ai/{model}"
-        model_info = litellm.model_cost.get(model_key, {})
-        return model_info.get("output_cost_per_second_1080p") is not None
+        model_key: Final = model if model.startswith("vertex_ai/") else f"vertex_ai/{model}"
+        model_info: Final = litellm.model_cost.get(model_key)
+        return model_info is not None and model_info.get("output_cost_per_second_1080p") is not None
 
     def validate_environment(
         self,
diff --git a/litellm/types/videos/main.py b/litellm/types/videos/main.py
index 4c57efe05b0..99b08f6caf6 100644
--- a/litellm/types/videos/main.py
+++ b/litellm/types/videos/main.py
@@ -2,7 +2,7 @@ from typing import Any, Literal
 
 from openai.types.audio.transcription_create_params import FileTypes
 from pydantic import BaseModel
-from typing_extensions import TypedDict
+from typing_extensions import ReadOnly, TypedDict
 
 
 class VideoObject(BaseModel):
@@ -76,7 +76,7 @@ class VideoCreateOptionalRequestParams(TypedDict, total=False):
     image: Any | None  # Image for image-to-video; dict with gcsUri/bytesBase64Encoded, or file-like object
     parameters: dict[str, Any] | None  # Provider-specific parameters block passed directly to the API
     model: str | None
-    resolution: str | None
+    resolution: ReadOnly[str | None]
     seconds: str | None
     size: str | None
     characters: list[dict[str, str]] | None