diff --git a/litellm/llms/voyage/embedding/transformation_contextual.py b/litellm/llms/voyage/embedding/transformation_contextual.py
index 870de8756bb..f5e7fdb48f5 100644
--- a/litellm/llms/voyage/embedding/transformation_contextual.py
+++ b/litellm/llms/voyage/embedding/transformation_contextual.py
@@ -11,7 +11,7 @@ import httpx
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.llms.base_llm.embedding.transformation import BaseEmbeddingConfig
-from litellm.secret_managers.main import get_secret_str
+from litellm.llms.voyage.common_utils import get_default_base_url, get_voyage_api_key
 from litellm.types.llms.openai import AllEmbeddingInputValues, AllMessageValues
 from litellm.types.utils import EmbeddingResponse, Usage
 
@@ -58,7 +58,7 @@ class VoyageContextualEmbeddingConfig(BaseEmbeddingConfig):
             if not api_base.endswith("/contextualizedembeddings"):
                 api_base = f"{api_base}/contextualizedembeddings"
             return api_base
-        return "https://api.voyageai.com/v1/contextualizedembeddings"
+        return f"{get_default_base_url(api_key)}/contextualizedembeddings"
 
     def get_supported_openai_params(self, model: str) -> list:  # mutable-ok: base class signature
         return ["encoding_format", "dimensions"]
@@ -91,14 +91,8 @@ class VoyageContextualEmbeddingConfig(BaseEmbeddingConfig):
         api_key: str | None = None,
         api_base: str | None = None,
     ) -> dict:
-        if api_key is None:
-            api_key = (
-                get_secret_str("VOYAGE_API_KEY")
-                or get_secret_str("VOYAGE_AI_API_KEY")
-                or get_secret_str("VOYAGE_AI_TOKEN")
-            )
         return {
-            "Authorization": f"Bearer {api_key}",
+            "Authorization": f"Bearer {get_voyage_api_key(api_key)}",
         }
 
     AUTO_CHUNK_SIZE: Final = 32000
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 7191a33a74a..afeb76c275e 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -60293,6 +60293,16 @@
         "output_vector_size": 1024,
         "source": "https://docs.voyageai.com/docs/pricing"
     },
+    "voyage/voyage-4-nano": {
+        "input_cost_per_token": 0.0,
+        "litellm_provider": "voyage",
+        "max_input_tokens": 32000,
+        "max_tokens": 32000,
+        "mode": "embedding",
+        "output_cost_per_token": 0.0,
+        "output_vector_size": 1024,
+        "source": "https://docs.voyageai.com/docs/embeddings"
+    },
     "voyage/voyage-code-4": {
         "input_cost_per_token": 1.2e-07,
         "litellm_provider": "voyage",
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 7191a33a74a..afeb76c275e 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -60293,6 +60293,16 @@
         "output_vector_size": 1024,
         "source": "https://docs.voyageai.com/docs/pricing"
     },
+    "voyage/voyage-4-nano": {
+        "input_cost_per_token": 0.0,
+        "litellm_provider": "voyage",
+        "max_input_tokens": 32000,
+        "max_tokens": 32000,
+        "mode": "embedding",
+        "output_cost_per_token": 0.0,
+        "output_vector_size": 1024,
+        "source": "https://docs.voyageai.com/docs/embeddings"
+    },
     "voyage/voyage-code-4": {
         "input_cost_per_token": 1.2e-07,
         "litellm_provider": "voyage",