diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 8df25d2c9b54..61e0dd079683 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -15551,14 +15551,17 @@
         "uses_embed_content": true
     },
     "vertex_ai/gemini-embedding-2-preview": {
-        "input_cost_per_token": 1.5e-07,
+        "input_cost_per_audio_per_second": 0.00016,
+        "input_cost_per_image": 0.00012,
+        "input_cost_per_token": 2e-07,
+        "input_cost_per_video_per_second": 0.00079,
         "litellm_provider": "vertex_ai",
         "max_input_tokens": 8192,
         "max_tokens": 8192,
         "mode": "embedding",
         "output_cost_per_token": 0,
         "output_vector_size": 3072,
-        "source": "https://ai.google.dev/gemini-api/docs/embeddings#multimodal",
+        "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing",
         "supports_multimodal": true,
         "uses_embed_content": true
     },
@@ -15573,7 +15576,7 @@
         "mode": "embedding",
         "output_cost_per_token": 0,
         "output_vector_size": 3072,
-        "source": "https://ai.google.dev/gemini-api/docs/embeddings#multimodal",
+        "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing",
         "supports_multimodal": true,
         "uses_embed_content": true
     },
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 70b065aa9181..e62f8686e9d5 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -15556,14 +15556,17 @@
         "uses_embed_content": true
     },
     "vertex_ai/gemini-embedding-2-preview": {
-        "input_cost_per_token": 1.5e-07,
+        "input_cost_per_audio_per_second": 0.00016,
+        "input_cost_per_image": 0.00012,
+        "input_cost_per_token": 2e-07,
+        "input_cost_per_video_per_second": 0.00079,
         "litellm_provider": "vertex_ai",
         "max_input_tokens": 8192,
         "max_tokens": 8192,
         "mode": "embedding",
         "output_cost_per_token": 0,
         "output_vector_size": 3072,
-        "source": "https://ai.google.dev/gemini-api/docs/embeddings#multimodal",
+        "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing",
         "supports_multimodal": true,
         "uses_embed_content": true
     },
@@ -15578,7 +15581,7 @@
         "mode": "embedding",
         "output_cost_per_token": 0,
         "output_vector_size": 3072,
-        "source": "https://ai.google.dev/gemini-api/docs/embeddings#multimodal",
+        "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing",
         "supports_multimodal": true,
         "uses_embed_content": true
     },
diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py
index d07af922ea68..bc60375f906b 100644
--- a/tests/test_litellm/test_utils.py
+++ b/tests/test_litellm/test_utils.py
@@ -3002,7 +3002,7 @@ def test_model_info_for_openrouter_kimi_k2_5():
 
 
 def test_gemini_embedding_2_ga_in_cost_map():
-    """GA gemini-embedding-2 entries align with preview multimodal unit pricing."""
+    """GA and Vertex preview gemini-embedding-2 entries align with multimodal unit pricing."""
     import json
     from pathlib import Path
 
@@ -3013,6 +3013,7 @@ def test_gemini_embedding_2_ga_in_cost_map():
     for key, provider in (
         ("gemini/gemini-embedding-2", "gemini"),
         ("vertex_ai/gemini-embedding-2", "vertex_ai"),
+        ("vertex_ai/gemini-embedding-2-preview", "vertex_ai"),
         ("gemini-embedding-2", "vertex_ai-embedding-models"),
     ):
         info = model_cost.get(key)