diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
index 5dd1b3c0bc6..db9cbe01432 100644
--- a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
@@ -1404,7 +1404,11 @@ class LiteLLMAnthropicMessagesAdapter:
 
     @staticmethod
     def _positive_int(value: object) -> int:
-        if isinstance(value, (int, float)) and not isinstance(value, bool) and value > 0:
+        if isinstance(value, bool):
+            return 0
+        if isinstance(value, int) and value > 0:
+            return value
+        if isinstance(value, float) and value.is_integer() and value > 0:
             return int(value)
         return 0
 
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py
index 9ae83eb831e..1d17cb93699 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py
@@ -2146,6 +2146,67 @@ def test_translate_openai_response_to_anthropic_cache_tokens_from_prompt_tokens_
     assert anthropic_response["usage"]["cache_read_input_tokens"] == 30
 
 
+def test_translate_openai_usage_to_anthropic_cache_tokens_from_dict_details_with_integral_floats():
+    usage = Usage(
+        prompt_tokens=120,
+        completion_tokens=50,
+        total_tokens=170,
+    )
+    usage.prompt_tokens_details = {
+        "cached_tokens": 30.0,
+        "cache_write_tokens": 20.0,
+    }
+
+    anthropic_usage = LiteLLMAnthropicMessagesAdapter._translate_openai_usage_to_anthropic_usage_delta(
+        usage
+    )
+
+    assert anthropic_usage["input_tokens"] == 70
+    assert anthropic_usage["output_tokens"] == 50
+    assert anthropic_usage["cache_read_input_tokens"] == 30
+    assert anthropic_usage["cache_creation_input_tokens"] == 20
+
+
+def test_translate_openai_usage_to_anthropic_ignores_fractional_cache_tokens():
+    usage = Usage(
+        prompt_tokens=120,
+        completion_tokens=50,
+        total_tokens=170,
+    )
+    usage.prompt_tokens_details = {
+        "cached_tokens": 30.5,
+        "cache_creation_tokens": 20.25,
+    }
+
+    anthropic_usage = LiteLLMAnthropicMessagesAdapter._translate_openai_usage_to_anthropic_usage_delta(
+        usage
+    )
+
+    assert anthropic_usage["input_tokens"] == 120
+    assert anthropic_usage["output_tokens"] == 50
+    assert "cache_read_input_tokens" not in anthropic_usage
+    assert "cache_creation_input_tokens" not in anthropic_usage
+
+
+def test_translate_openai_usage_to_anthropic_ignores_bool_cache_tokens():
+    usage = Usage(
+        prompt_tokens=120,
+        completion_tokens=50,
+        total_tokens=170,
+    )
+    usage.cache_read_input_tokens = True
+    usage.cache_creation_input_tokens = True
+
+    anthropic_usage = LiteLLMAnthropicMessagesAdapter._translate_openai_usage_to_anthropic_usage_delta(
+        usage
+    )
+
+    assert anthropic_usage["input_tokens"] == 120
+    assert anthropic_usage["output_tokens"] == 50
+    assert "cache_read_input_tokens" not in anthropic_usage
+    assert "cache_creation_input_tokens" not in anthropic_usage
+
+
 def test_translate_openai_response_to_anthropic_cache_creation_from_prompt_tokens_details():
     from litellm.types.utils import PromptTokensDetailsWrapper
 
@@ -2288,6 +2349,41 @@ def test_translate_streaming_openai_response_to_anthropic_cache_tokens_from_prom
     assert message_delta["usage"]["cache_creation_input_tokens"] == 20
 
 
+def test_translate_streaming_openai_response_to_anthropic_cache_tokens_from_hidden_params_usage():
+    from litellm.types.utils import PromptTokensDetailsWrapper
+
+    usage = Usage(
+        prompt_tokens=120,
+        completion_tokens=50,
+        total_tokens=170,
+        prompt_tokens_details=PromptTokensDetailsWrapper(
+            cached_tokens=30,
+            cache_creation_tokens=20,
+        ),
+    )
+    response = ModelResponseStream(
+        choices=[
+            StreamingChoices(
+                index=0,
+                delta=Delta(),
+                finish_reason="stop",
+            )
+        ],
+    )
+    response._hidden_params = {"usage": usage}
+
+    adapter = LiteLLMAnthropicMessagesAdapter()
+    message_delta = adapter.translate_streaming_openai_response_to_anthropic(
+        response=response,
+        current_content_block_index=0,
+    )
+
+    assert message_delta["usage"]["input_tokens"] == 70
+    assert message_delta["usage"]["output_tokens"] == 50
+    assert message_delta["usage"]["cache_read_input_tokens"] == 30
+    assert message_delta["usage"]["cache_creation_input_tokens"] == 20
+
+
 # =====================================================================
 # Web Search Tool Transformation Tests
 # =====================================================================