From a05c6e6f183e599ccc79276bd3bc3d43964e1753 Mon Sep 17 00:00:00 2001
From: Alphaxiaoteng <230277249+Alphaxiaoteng@users.noreply.github.com>
Date: Thu, 3 Sep 2026 16:23:39 +0800
Subject: [PATCH] fix: keep top-level cache token counts with partial usage
 details

OpenAI-compatible responses can send cache_read_input_tokens alongside a
partial prompt_tokens_details object. Prefer details only when they
explicitly include cached_tokens so a missing key no longer wipes the
top-level cache count to 0 (#39505).

Co-authored-by: Cursor <cursoragent@cursor.com>
---
 litellm/cost_calculator.py                  | 21 +++++++++-
 tests/local_testing/test_completion_cost.py | 45 +++++++++++++++++++++
 2 files changed, 65 insertions(+), 1 deletion(-)

diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py
index b83e9b395a8..b5189d96935 100644
--- a/litellm/cost_calculator.py
+++ b/litellm/cost_calculator.py
@@ -1343,7 +1343,26 @@ def completion_cost(
                         and _usage["prompt_tokens_details"]
                     ):
                         prompt_tokens_details = _usage.get("prompt_tokens_details") or {}
-                        cache_read_input_tokens = prompt_tokens_details.get("cached_tokens", 0)
+                        # Only prefer details when they actually carry cached_tokens.
+                        # OpenAI-compatible providers often send both top-level
+                        # cache_read_input_tokens and a partial prompt_tokens_details
+                        # object (e.g. audio_tokens only). Using `.get(..., 0)` would
+                        # wipe the top-level cache count with a default of 0 (#39505).
+                        if (
+                            isinstance(prompt_tokens_details, dict)
+                            and "cached_tokens" in prompt_tokens_details
+                            and prompt_tokens_details["cached_tokens"] is not None
+                        ):
+                            cache_read_input_tokens = prompt_tokens_details["cached_tokens"]
+                        if (
+                            isinstance(prompt_tokens_details, dict)
+                            and not cache_creation_input_tokens
+                        ):
+                            cache_write_tokens = prompt_tokens_details.get(
+                                "cache_write_tokens"
+                            ) or prompt_tokens_details.get("cache_creation_tokens")
+                            if isinstance(cache_write_tokens, int):
+                                cache_creation_input_tokens = cache_write_tokens
 
                     total_time = getattr(completion_response, "_response_ms", 0)
 
diff --git a/tests/local_testing/test_completion_cost.py b/tests/local_testing/test_completion_cost.py
index f47b40f2ef1..222708eb343 100644
--- a/tests/local_testing/test_completion_cost.py
+++ b/tests/local_testing/test_completion_cost.py
@@ -2928,3 +2928,48 @@ def test_batch_cost_calculator():
 
     cost = completion_cost(**args)
     assert cost > 0
+
+
+def test_openai_compatible_top_level_cache_tokens_survive_partial_details(monkeypatch):
+    """Regression for #39505.
+
+    OpenAI-compatible providers may return top-level cache_read_input_tokens
+    together with a partial prompt_tokens_details object that omits
+    cached_tokens. The details branch must not default-wipe the top-level
+    cache count to 0.
+    """
+    captured = {}
+
+    def _fake_cost_per_token(**kwargs):
+        captured.update(kwargs)
+        return 0.01, 0.02
+
+    monkeypatch.setattr(litellm.cost_calculator, "cost_per_token", _fake_cost_per_token)
+    monkeypatch.setattr(litellm, "cost_per_token", _fake_cost_per_token)
+
+    response = {
+        "id": "chatcmpl-test-cache",
+        "object": "chat.completion",
+        "created": 1,
+        "model": "gpt-4o",
+        "choices": [
+            {
+                "index": 0,
+                "message": {"role": "assistant", "content": "ok"},
+                "finish_reason": "stop",
+            }
+        ],
+        "usage": {
+            "prompt_tokens": 100,
+            "completion_tokens": 10,
+            "total_tokens": 110,
+            "cache_read_input_tokens": 80,
+            "cache_creation_input_tokens": 5,
+            "prompt_tokens_details": {"audio_tokens": 0},
+        },
+    }
+
+    cost = completion_cost(model="gpt-4o", completion_response=response)
+    assert cost == 0.03
+    assert captured.get("cache_read_input_tokens") == 80
+    assert captured.get("cache_creation_input_tokens") == 5