diff --git a/litellm/integrations/langfuse/langfuse.py b/litellm/integrations/langfuse/langfuse.py
index f0f355b489..7e62613a7e 100644
--- a/litellm/integrations/langfuse/langfuse.py
+++ b/litellm/integrations/langfuse/langfuse.py
@@ -50,6 +50,42 @@ else:
     Langfuse = Any
 
 
+def _extract_cache_read_input_tokens(usage_obj) -> int:
+    """
+    Extract cache_read_input_tokens from usage object.
+
+    Checks both:
+    1. Top-level cache_read_input_tokens (Anthropic format)
+    2. prompt_tokens_details.cached_tokens (Gemini, OpenAI format)
+
+    See: https://github.com/BerriAI/litellm/issues/18520
+
+    Args:
+        usage_obj: Usage object from LLM response
+
+    Returns:
+        int: Number of cached tokens read, defaults to 0
+    """
+    cache_read_input_tokens = usage_obj.get("cache_read_input_tokens") or 0
+
+    # Check prompt_tokens_details.cached_tokens (used by Gemini and other providers)
+    if hasattr(usage_obj, "prompt_tokens_details"):
+        prompt_tokens_details = getattr(usage_obj, "prompt_tokens_details", None)
+        if (
+            prompt_tokens_details is not None
+            and hasattr(prompt_tokens_details, "cached_tokens")
+        ):
+            cached_tokens = getattr(prompt_tokens_details, "cached_tokens", None)
+            if (
+                cached_tokens is not None
+                and isinstance(cached_tokens, (int, float))
+                and cached_tokens > 0
+            ):
+                cache_read_input_tokens = cached_tokens
+
+    return cache_read_input_tokens
+
+
 class LangFuseLogger:
     # Class variables or attributes
     def __init__(
@@ -757,8 +793,8 @@ class LangFuseLogger:
                     cache_creation_input_tokens = (
                         _usage_obj.get("cache_creation_input_tokens") or 0
                     )
-                    cache_read_input_tokens = (
-                        _usage_obj.get("cache_read_input_tokens") or 0
+                    cache_read_input_tokens = _extract_cache_read_input_tokens(
+                        _usage_obj
                     )
 
                     usage = {
diff --git a/tests/test_litellm/integrations/langfuse/test_gemini_cached_tokens.py b/tests/test_litellm/integrations/langfuse/test_gemini_cached_tokens.py
new file mode 100644
index 0000000000..e717840ec9
--- /dev/null
+++ b/tests/test_litellm/integrations/langfuse/test_gemini_cached_tokens.py
@@ -0,0 +1,90 @@
+"""
+Test for Langfuse integration with Gemini cached_tokens bug
+https://github.com/BerriAI/litellm/issues/18520
+"""
+import pytest
+from litellm.types.utils import PromptTokensDetailsWrapper, Usage
+
+
+def test_cached_tokens_extraction():
+    """
+    Test that we can extract cached_tokens from prompt_tokens_details.
+    This is the core logic fix for https://github.com/BerriAI/litellm/issues/18520
+    """
+    # Create usage object like Gemini returns
+    usage = Usage(
+        prompt_tokens=20209,
+        prompt_tokens_details=PromptTokensDetailsWrapper(
+            cached_tokens=20203,
+            text_tokens=6,
+        ),
+        completion_tokens=541,
+    )
+
+    # Simulate the logic from langfuse.py lines 745-757 (after the fix)
+    cache_read_input_tokens = 0  # Default value
+
+    # Check prompt_tokens_details.cached_tokens (the fix)
+    if hasattr(usage, "prompt_tokens_details"):
+        prompt_tokens_details = getattr(usage, "prompt_tokens_details", None)
+        if (
+            prompt_tokens_details is not None
+            and hasattr(prompt_tokens_details, "cached_tokens")
+        ):
+            cached_tokens = getattr(prompt_tokens_details, "cached_tokens", None)
+            if cached_tokens is not None and cached_tokens > 0:
+                cache_read_input_tokens = cached_tokens
+
+    # Verify the fix works
+    assert cache_read_input_tokens == 20203, f"Expected 20203, got {cache_read_input_tokens}"
+
+
+def test_cached_tokens_not_present():
+    """Test backward compatibility when cached_tokens is not present"""
+    # Usage without prompt_tokens_details
+    usage = Usage(
+        prompt_tokens=100,
+        completion_tokens=50,
+    )
+
+    cache_read_input_tokens = 0
+
+    if hasattr(usage, "prompt_tokens_details"):
+        prompt_tokens_details = getattr(usage, "prompt_tokens_details", None)
+        if (
+            prompt_tokens_details is not None
+            and hasattr(prompt_tokens_details, "cached_tokens")
+        ):
+            cached_tokens = getattr(prompt_tokens_details, "cached_tokens", None)
+            if cached_tokens is not None and cached_tokens > 0:
+                cache_read_input_tokens = cached_tokens
+
+    # Should remain 0
+    assert cache_read_input_tokens == 0
+
+
+def test_cached_tokens_is_zero():
+    """Test when cached_tokens is explicitly 0"""
+    usage = Usage(
+        prompt_tokens=100,
+        prompt_tokens_details=PromptTokensDetailsWrapper(
+            cached_tokens=0,
+            text_tokens=100,
+        ),
+        completion_tokens=50,
+    )
+
+    cache_read_input_tokens = 0
+
+    if hasattr(usage, "prompt_tokens_details"):
+        prompt_tokens_details = getattr(usage, "prompt_tokens_details", None)
+        if (
+            prompt_tokens_details is not None
+            and hasattr(prompt_tokens_details, "cached_tokens")
+        ):
+            cached_tokens = getattr(prompt_tokens_details, "cached_tokens", None)
+            if cached_tokens is not None and cached_tokens > 0:
+                cache_read_input_tokens = cached_tokens
+
+    # Should remain 0 when cached_tokens is 0
+    assert cache_read_input_tokens == 0