diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py
index 3dc6d81256b..852713595d5 100644
--- a/litellm/cost_calculator.py
+++ b/litellm/cost_calculator.py
@@ -814,6 +814,7 @@ def _select_model_name_for_cost_calc(
             if (
                 entry.get("input_cost_per_token") is not None
                 or entry.get("input_cost_per_second") is not None
+                or entry.get("input_cost_per_query") is not None
                 or entry.get("tiered_pricing") is not None
             ):
                 return_model = router_model_id
diff --git a/litellm/llms/fireworks_ai/rerank/transformation.py b/litellm/llms/fireworks_ai/rerank/transformation.py
index e142622aa1b..509dbd5ff24 100644
--- a/litellm/llms/fireworks_ai/rerank/transformation.py
+++ b/litellm/llms/fireworks_ai/rerank/transformation.py
@@ -250,8 +250,7 @@ class FireworksAIRerankConfig(FireworksAIMixin, BaseRerankConfig):
 
             rerank_results.append(rerank_result)
 
-        # Use model name as id if no id is provided
-        response_id: Final = raw_response_json.get("id") or raw_response_json.get("model") or str(uuid.uuid4())
+        response_id: Final = raw_response_json.get("id") or str(uuid.uuid4())
 
         return RerankResponse(
             id=response_id,
diff --git a/litellm/llms/vertex_ai/rerank/transformation.py b/litellm/llms/vertex_ai/rerank/transformation.py
index 2ec4f2da79b..b0c6add69fd 100644
--- a/litellm/llms/vertex_ai/rerank/transformation.py
+++ b/litellm/llms/vertex_ai/rerank/transformation.py
@@ -4,6 +4,8 @@ Translates from Cohere's `/v1/rerank` input format to Vertex AI Discovery Engine
 Why separate file? Make it easy to see how transformation works
 """
 
+import math
+import uuid
 from collections.abc import Mapping
 from typing import Any, Final
 
@@ -32,6 +34,8 @@ class VertexAIRerankConfig(BaseRerankConfig, VertexBase):
     Reference: https://cloud.google.com/generative-ai-app-builder/docs/ranking#rank_or_rerank_a_set_of_records_according_to_a_query
     """
 
+    MAX_RECORDS_PER_SEARCH_UNIT = 100
+
     def __init__(self) -> None:
         super().__init__()
 
@@ -208,10 +212,11 @@ class VertexAIRerankConfig(BaseRerankConfig, VertexBase):
                 RerankResponseResult(index=result["index"], relevance_score=result["relevance_score"])
             )
 
-        # Create meta object
-        meta: Final = RerankResponseMeta(billed_units=RerankBilledUnits(search_units=len(records)))
+        input_record_count: Final = len(request_data.get("records", ()))
+        search_units: Final = math.ceil(input_record_count / self.MAX_RECORDS_PER_SEARCH_UNIT)
+        meta: Final = RerankResponseMeta(billed_units=RerankBilledUnits(search_units=search_units))
 
-        return RerankResponse(id=f"vertex_ai_rerank_{model}", results=rerank_results, meta=meta)
+        return RerankResponse(id=f"vertex_ai_rerank_{uuid.uuid4()}", results=rerank_results, meta=meta)
 
     def get_supported_cohere_rerank_params(self, model: str) -> list:
         return [
diff --git a/litellm/llms/voyage/rerank/transformation.py b/litellm/llms/voyage/rerank/transformation.py
index fea8452d934..0f57ac11028 100644
--- a/litellm/llms/voyage/rerank/transformation.py
+++ b/litellm/llms/voyage/rerank/transformation.py
@@ -9,6 +9,7 @@ from typing import Any, Final
 
 import httpx
 
+from litellm._uuid import uuid
 from litellm.llms.base_llm.chat.transformation import LiteLLMLoggingObj
 from litellm.llms.base_llm.rerank.transformation import BaseRerankConfig
 from litellm.secret_managers.main import get_secret_str
@@ -127,7 +128,7 @@ class VoyageRerankConfig(BaseRerankConfig):
         rerank_meta: Final = RerankResponseMeta(billed_units=_billed_units, tokens=_tokens)
 
         return RerankResponse(
-            id=_json_response.get("id", f"voyage-rerank-{model}"),
+            id=_json_response.get("id") or str(uuid.uuid4()),
             results=transformed_results,
             meta=rerank_meta,
         )
diff --git a/litellm/llms/watsonx/rerank/transformation.py b/litellm/llms/watsonx/rerank/transformation.py
index 293880b188d..bd6b23ff2be 100644
--- a/litellm/llms/watsonx/rerank/transformation.py
+++ b/litellm/llms/watsonx/rerank/transformation.py
@@ -191,7 +191,7 @@ class IBMWatsonXRerankConfig(IBMWatsonXMixin, BaseRerankConfig):
 
             transformed_results.append(transformed_result)
 
-        response_id: Final = raw_response_json.get("id") or raw_response_json.get("model_id") or str(uuid.uuid4())
+        response_id: Final = raw_response_json.get("id") or str(uuid.uuid4())
 
         # Extract usage information
         _tokens: Final = RerankTokens(
diff --git a/tests/test_litellm/llms/fireworks_ai/rerank/test_fireworks_ai_rerank_transformation.py b/tests/test_litellm/llms/fireworks_ai/rerank/test_fireworks_ai_rerank_transformation.py
index 521ea4f8263..a03b7708238 100644
--- a/tests/test_litellm/llms/fireworks_ai/rerank/test_fireworks_ai_rerank_transformation.py
+++ b/tests/test_litellm/llms/fireworks_ai/rerank/test_fireworks_ai_rerank_transformation.py
@@ -3,6 +3,7 @@ Tests for Fireworks AI rerank transformation functionality.
 """
 
 import json
+import uuid
 from unittest.mock import MagicMock
 
 import httpx
@@ -181,8 +182,7 @@ class TestFireworksAIRerankTransform:
         )
 
         # Verify response structure
-        # Fireworks AI doesn't return "id", so it uses "model" as the id
-        assert result.id == "accounts/fireworks/models/qwen3-reranker-8b"
+        assert uuid.UUID(result.id).version == 4
         assert len(result.results) == 2
         assert result.results[0]["index"] == 0
         assert result.results[0]["relevance_score"] == 0.95
@@ -229,16 +229,14 @@ class TestFireworksAIRerankTransform:
             logging_obj=mock_logging,
         )
 
-        # Fireworks AI doesn't return "id", so it uses "model" as the id
-        assert result.id == "accounts/fireworks/models/qwen3-reranker-8b"
+        assert uuid.UUID(result.id).version == 4
         assert len(result.results) == 2
         assert result.results[0]["index"] == 0
         assert result.results[0]["relevance_score"] == 0.95
         # Document should not be present
         assert "document" not in result.results[0]
 
-    def test_transform_rerank_response_missing_id(self):
-        """Test response transformation when id is missing (should use model name or generate UUID)."""
+    def test_transform_rerank_response_missing_id_stamps_a_fresh_id_per_call(self):
         response_data = {
             "object": "list",
             "model": "accounts/fireworks/models/qwen3-reranker-8b",
@@ -248,23 +246,22 @@ class TestFireworksAIRerankTransform:
             "usage": {"total_tokens": 10},
         }
 
-        mock_response = MagicMock(spec=httpx.Response)
-        mock_response.json.return_value = response_data
-        mock_response.status_code = 200
-        mock_response.headers = {}
+        def transform() -> str:
+            mock_response = MagicMock(spec=httpx.Response)
+            mock_response.json.return_value = response_data
+            mock_response.status_code = 200
+            mock_response.headers = {}
+            return self.config.transform_rerank_response(
+                model=self.model,
+                raw_response=mock_response,
+                model_response=RerankResponse(),
+                logging_obj=MagicMock(),
+            ).id
 
-        mock_logging = MagicMock()
-        model_response = RerankResponse()
+        first, second = transform(), transform()
 
-        result = self.config.transform_rerank_response(
-            model=self.model,
-            raw_response=mock_response,
-            model_response=model_response,
-            logging_obj=mock_logging,
-        )
-
-        # Should use model name when id is missing
-        assert result.id == "accounts/fireworks/models/qwen3-reranker-8b"
+        assert first != second
+        assert "accounts/fireworks/models/qwen3-reranker-8b" not in (first, second)
 
     def test_transform_rerank_response_missing_results(self):
         """Test that missing results raises ValueError."""
diff --git a/tests/test_litellm/llms/vertex_ai/rerank/test_vertex_ai_rerank_integration.py b/tests/test_litellm/llms/vertex_ai/rerank/test_vertex_ai_rerank_integration.py
index 7fea5ac0965..3ec734611ef 100644
--- a/tests/test_litellm/llms/vertex_ai/rerank/test_vertex_ai_rerank_integration.py
+++ b/tests/test_litellm/llms/vertex_ai/rerank/test_vertex_ai_rerank_integration.py
@@ -104,10 +104,12 @@ class TestVertexAIRerankIntegration:
             raw_response=mock_response,
             model_response=model_response,
             logging_obj=mock_logging,
+            request_data=request_data,
         )
 
         # Verify response structure
-        assert result.id == f"vertex_ai_rerank_{self.model}"
+        assert result.id.startswith("vertex_ai_rerank_")
+        assert result.id != f"vertex_ai_rerank_{self.model}"
         assert len(result.results) == 2
 
         # Results should be sorted by relevance score (descending)
@@ -116,8 +118,8 @@ class TestVertexAIRerankIntegration:
         assert result.results[1]["index"] == 0  # Second highest score
         assert result.results[1]["relevance_score"] == 0.92
 
-        # Verify metadata
-        assert result.meta["billed_units"]["search_units"] == 2
+        # Verify metadata: 4 input records bill as 1 search unit (ceil(4/100))
+        assert result.meta["billed_units"]["search_units"] == 1
 
     def test_return_documents_false_flow(self):
         """Test rerank flow when return_documents=False (ID-only response)."""
diff --git a/tests/test_litellm/llms/vertex_ai/rerank/test_vertex_ai_rerank_transformation.py b/tests/test_litellm/llms/vertex_ai/rerank/test_vertex_ai_rerank_transformation.py
index c2ea6f6fab9..630b2e1eb34 100644
--- a/tests/test_litellm/llms/vertex_ai/rerank/test_vertex_ai_rerank_transformation.py
+++ b/tests/test_litellm/llms/vertex_ai/rerank/test_vertex_ai_rerank_transformation.py
@@ -287,10 +287,11 @@ class TestVertexAIRerankTransform:
             raw_response=mock_response,
             model_response=model_response,
             logging_obj=mock_logging,
+            request_data={"records": [{"id": "0"}, {"id": "1"}]},
         )
 
         # Verify response structure
-        assert result.id == f"vertex_ai_rerank_{self.model}"
+        assert result.id.startswith("vertex_ai_rerank_")
         assert len(result.results) == 2
         assert result.results[0]["index"] == 1  # Converted back to 0-based index
         assert result.results[0]["relevance_score"] == 0.98
@@ -298,7 +299,7 @@ class TestVertexAIRerankTransform:
         assert result.results[1]["relevance_score"] == 0.64
 
         # Verify metadata
-        assert result.meta["billed_units"]["search_units"] == 2
+        assert result.meta["billed_units"]["search_units"] == 1
 
     def test_transform_rerank_response_with_ignore_record_details(self):
         """Test response transformation when ignoreRecordDetailsInResponse=true."""
@@ -326,6 +327,96 @@ class TestVertexAIRerankTransform:
         assert result.results[1]["index"] == 0
         assert result.results[1]["relevance_score"] == 1.0
 
+    def _build_response(self, num_records):
+        response_data = {
+            "records": [
+                {"id": str(i), "score": 1.0 - i / 1000, "title": "t", "content": "c"}
+                for i in range(num_records)
+            ]
+        }
+        mock_response = MagicMock(spec=httpx.Response)
+        mock_response.json.return_value = response_data
+        mock_response.text = json.dumps(response_data)
+        return mock_response
+
+    def test_search_units_from_input_records_not_truncated_response(self):
+        """
+        Regression for LIT-4995 part 1: search_units must be derived from the
+        billable input records (ceil(input / 100)), not from the response, which
+        Google truncates to topN.
+        """
+        documents = [f"doc {i}" for i in range(5)]
+        request_data = self.config.transform_rerank_request(
+            model=self.model,
+            optional_rerank_params={"query": "q", "documents": documents, "top_n": 2},
+            headers={},
+        )
+        # Google truncates the response to top_n=2 records
+        mock_response = self._build_response(num_records=2)
+
+        result = self.config.transform_rerank_response(
+            model=self.model,
+            raw_response=mock_response,
+            model_response=RerankResponse(),
+            logging_obj=MagicMock(),
+            request_data=request_data,
+        )
+
+        assert result.meta["billed_units"]["search_units"] == 1
+
+    def test_search_units_rounds_up_per_hundred_input_records(self):
+        """
+        Regression for LIT-4995 part 1: one query bills up to 100 input records,
+        so 150 input records is 2 search units regardless of the response size.
+        """
+        documents = [f"doc {i}" for i in range(150)]
+        request_data = self.config.transform_rerank_request(
+            model=self.model,
+            optional_rerank_params={"query": "q", "documents": documents, "top_n": 3},
+            headers={},
+        )
+        mock_response = self._build_response(num_records=3)
+
+        result = self.config.transform_rerank_response(
+            model=self.model,
+            raw_response=mock_response,
+            model_response=RerankResponse(),
+            logging_obj=MagicMock(),
+            request_data=request_data,
+        )
+
+        assert result.meta["billed_units"]["search_units"] == 2
+
+    def test_response_id_is_unique_per_request(self):
+        """
+        Regression for LIT-4995 part 2: response IDs must be unique per request,
+        not a constant derived only from the model name.
+        """
+        request_data = self.config.transform_rerank_request(
+            model=self.model,
+            optional_rerank_params={"query": "q", "documents": ["a", "b"]},
+            headers={},
+        )
+        mock_response = self._build_response(num_records=2)
+
+        first = self.config.transform_rerank_response(
+            model=self.model,
+            raw_response=mock_response,
+            model_response=RerankResponse(),
+            logging_obj=MagicMock(),
+            request_data=request_data,
+        )
+        second = self.config.transform_rerank_response(
+            model=self.model,
+            raw_response=mock_response,
+            model_response=RerankResponse(),
+            logging_obj=MagicMock(),
+            request_data=request_data,
+        )
+
+        assert first.id != second.id
+        assert first.id != f"vertex_ai_rerank_{self.model}"
+
     def test_transform_rerank_response_json_error(self):
         """Test response transformation with JSON parsing error."""
         mock_response = MagicMock(spec=httpx.Response)
diff --git a/tests/test_litellm/llms/voyage/rerank/test_voyage_rerank_transformation.py b/tests/test_litellm/llms/voyage/rerank/test_voyage_rerank_transformation.py
index f466b7e19b5..5eb4bf31845 100644
--- a/tests/test_litellm/llms/voyage/rerank/test_voyage_rerank_transformation.py
+++ b/tests/test_litellm/llms/voyage/rerank/test_voyage_rerank_transformation.py
@@ -3,6 +3,7 @@ Tests for Voyage AI rerank transformation functionality.
 """
 
 import json
+import uuid
 from unittest.mock import MagicMock, patch
 
 import httpx
@@ -258,6 +259,33 @@ class TestVoyageRerankTransform:
 
         assert "Failed to parse response" in str(exc_info.value)
 
+    def test_transform_rerank_response_without_id_stamps_a_fresh_id_per_call(self):
+        response_data = {
+            "object": "list",
+            "data": [{"relevance_score": 0.5, "index": 0}],
+            "model": "rerank-2.5",
+            "usage": {"total_tokens": 10},
+        }
+
+        def transform() -> str:
+            mock_response = MagicMock(spec=httpx.Response)
+            mock_response.json.return_value = response_data
+            mock_response.status_code = 200
+            mock_response.text = json.dumps(response_data)
+            mock_response.headers = {}
+            return self.config.transform_rerank_response(
+                model=self.model,
+                raw_response=mock_response,
+                model_response=RerankResponse(),
+                logging_obj=MagicMock(),
+            ).id
+
+        first, second = transform(), transform()
+
+        assert uuid.UUID(first).version == 4
+        assert first != second
+        assert f"voyage-rerank-{self.model}" not in (first, second)
+
     def test_get_supported_cohere_rerank_params(self):
         """Test getting supported parameters for Voyage AI rerank."""
         supported_params = self.config.get_supported_cohere_rerank_params(self.model)
diff --git a/tests/test_litellm/llms/watsonx/rerank/test_watsonx_rerank.py b/tests/test_litellm/llms/watsonx/rerank/test_watsonx_rerank.py
index c8f2c4dd87c..ccbd318959f 100644
--- a/tests/test_litellm/llms/watsonx/rerank/test_watsonx_rerank.py
+++ b/tests/test_litellm/llms/watsonx/rerank/test_watsonx_rerank.py
@@ -120,9 +120,7 @@ class TestIBMWatsonXRerankTransform:
             logging_obj=mock_logging,
         )
 
-        # Verify response structure
-        # IBM watsonx.ai doesn't return "id", so it uses "model" as the id
-        assert result.id == "watsonx/cross-encoder/ms-marco-minilm-l-12-v2"
+        assert uuid.UUID(result.id).version == 4
         assert len(result.results) == 2
         assert result.results[0]["index"] == 0
         assert result.results[0]["relevance_score"] == 6.53515625
@@ -172,9 +170,7 @@ class TestIBMWatsonXRerankTransform:
             logging_obj=mock_logging,
         )
 
-        # Verify response structure
-        # IBM watsonx.ai doesn't return "id", so it uses "model" as the id
-        assert result.id == "watsonx/cross-encoder/ms-marco-minilm-l-12-v2"
+        assert uuid.UUID(result.id).version == 4
         assert len(result.results) == 2
 
         assert result.results[0]["index"] == 0
@@ -231,6 +227,30 @@ class TestIBMWatsonXRerankTransform:
                 logging_obj=mock_logging,
             )
 
+    def test_transform_rerank_response_without_id_stamps_a_fresh_id_per_call(self):
+        response_data = {
+            "model_id": self.model,
+            "results": [{"index": 0, "score": 1.5}],
+            "input_token_count": 12,
+        }
+
+        def transform() -> str:
+            mock_response = MagicMock(spec=httpx.Response)
+            mock_response.json.return_value = response_data
+            mock_response.status_code = 200
+            mock_response.headers = {}
+            return self.config.transform_rerank_response(
+                model=self.model,
+                raw_response=mock_response,
+                model_response=RerankResponse(),
+                logging_obj=MagicMock(),
+            ).id
+
+        first, second = transform(), transform()
+
+        assert first != second
+        assert self.model not in (first, second)
+
     def test_get_supported_cohere_rerank_params(self):
         """Test getting supported parameters for IBM watsonx.ai rerank."""
         supported_params = self.config.get_supported_cohere_rerank_params(self.model)
diff --git a/tests/test_litellm/test_cost_calculator.py b/tests/test_litellm/test_cost_calculator.py
index cbbd5aa6eb6..ef797ef8bcc 100644
--- a/tests/test_litellm/test_cost_calculator.py
+++ b/tests/test_litellm/test_cost_calculator.py
@@ -1211,6 +1211,47 @@ def test_tiered_pricing_only_deployment_completion_cost_is_nonzero():
     assert cost > 0
 
 
+def test_per_query_priced_rerank_deployment_completion_cost_is_nonzero():
+    """A rerank deployment priced only via ``input_cost_per_query`` must resolve
+    cost against its ``router_model_id`` entry: the shared backend alias has
+    custom pricing stripped, so pricing it there bills every search unit as $0.
+    """
+    from litellm import Router
+
+    router: Final = Router(
+        model_list=[
+            {
+                "model_name": "semantic-ranker-default-004",
+                "litellm_params": {
+                    "model": "vertex_ai/semantic-ranker-default-004",
+                    "vertex_project": "test-project",
+                    "vertex_location": "us-east5",
+                },
+                "model_info": {"input_cost_per_query": 0.001},
+            },
+        ]
+    )
+    router_model_id: Final = router.model_list[0]["model_info"]["id"]
+    assert litellm.model_cost["vertex_ai/semantic-ranker-default-004"].get("input_cost_per_query") is None
+
+    response: Final = RerankResponse(
+        id="vertex_ai_rerank_test",
+        results=[{"index": 3, "relevance_score": 0.48}],
+        meta={"billed_units": {"search_units": 3}},
+    )
+
+    cost: Final = completion_cost(
+        completion_response=response,
+        model="vertex_ai/semantic-ranker-default-004",
+        custom_llm_provider="vertex_ai",
+        call_type="arerank",
+        custom_pricing=True,
+        router_model_id=router_model_id,
+    )
+
+    assert cost == pytest.approx(3 * 0.001)
+
+
 def test_azure_realtime_cost_calculator(_local_model_cost_map):
 
     cost = handle_realtime_stream_cost_calculation(