fix(bedrock): parse cacheDetails for Converse 1h/5m cache write cost split

litellm/llms/bedrock/chat/converse_transformation.py

@@ -65,6 +65,7 @@
     OpenAIMessageContentListBlock,
 )
 from litellm.types.utils import (
+    CacheCreationTokenDetails,
     ChatCompletionMessageToolCall,
     CompletionTokensDetailsWrapper,
     Function,
@@ -1807,6 +1808,26 @@ def _transform_thinking_blocks(
                 thinking_blocks_list.append(_redacted_block)
         return thinking_blocks_list
 
+    @staticmethod
+    def _parse_cache_details(usage: ConverseTokenUsageBlock) -> "CacheCreationTokenDetails | None":
+        """Split ``cacheDetails`` into 5m/1h buckets, or ``None`` unless the split fully
+        accounts for ``cacheWriteInputTokens``, since a partial or unrecognized-ttl
+        breakdown would understate the cache-write cost.
+
+        https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_CacheDetail.html
+        """
+        cache_details: Final = usage.get("cacheDetails")
+        if not cache_details:
+            return None
+        tokens_5m: Final = sum(d["inputTokens"] for d in cache_details if d.get("ttl") == "5m")
+        tokens_1h: Final = sum(d["inputTokens"] for d in cache_details if d.get("ttl") == "1h")
+        if tokens_5m + tokens_1h != usage.get("cacheWriteInputTokens", 0):
+            return None
+        return CacheCreationTokenDetails(
+            ephemeral_5m_input_tokens=tokens_5m,
+            ephemeral_1h_input_tokens=tokens_1h,
+        )
+
     @staticmethod
     def thinking_tokens_from_additional_fields(additional_fields: object) -> int | None:
         """Converse omits thinking tokens from its usage block; they only arrive under
@@ -1878,6 +1899,7 @@ def transform_usage(
         prompt_tokens_details: Final = PromptTokensDetailsWrapper(
             cached_tokens=cache_read_input_tokens,
             cache_creation_tokens=cache_creation_input_tokens,
+            cache_creation_token_details=self._parse_cache_details(usage),
             text_tokens=raw_input_tokens,
         )
         estimated_reasoning_tokens: Final = (

litellm/types/llms/bedrock.py

@@ -221,14 +221,22 @@ class ConverseResponseOutputBlock(TypedDict):
     message: MessageBlock | None
 
 
-class ConverseTokenUsageBlock(TypedDict):
-    inputTokens: int
-    outputTokens: int
-    totalTokens: int
-    cacheReadInputTokenCount: int
-    cacheReadInputTokens: int
-    cacheWriteInputTokenCount: int
-    cacheWriteInputTokens: int
+class CacheDetailBlock(TypedDict):
+    """Per-TTL cache-write breakdown, read-only AWS response data. https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_CacheDetail.html"""
+
+    inputTokens: ReadOnly[int]
+    ttl: ReadOnly[Literal["5m", "1h"]]
+
+
+class ConverseTokenUsageBlock(TypedDict, total=False):
+    inputTokens: Required[ReadOnly[int]]
+    outputTokens: Required[ReadOnly[int]]
+    totalTokens: Required[ReadOnly[int]]
+    cacheReadInputTokenCount: ReadOnly[int]
+    cacheReadInputTokens: ReadOnly[int]
+    cacheWriteInputTokenCount: ReadOnly[int]
+    cacheWriteInputTokens: ReadOnly[int]
+    cacheDetails: ReadOnly[list[CacheDetailBlock]]  # mutable-ok: AWS response array, never mutated after parsing
 
 
 class ServiceTierBlock(TypedDict):

tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py

@@ -47,6 +47,97 @@ def test_transform_usage():
     assert openai_usage.completion_tokens_details.text_tokens == usage["outputTokens"]
 
 
+def test_transform_usage_with_cache_details():
+    """cacheDetails should split cacheWriteInputTokens into the 5m/1h TTL breakdown
+    so cost calc can bill the 1h portion at its own (higher) rate instead of
+    defaulting the whole write to the 5m rate. See issue #36760."""
+    usage = ConverseTokenUsageBlock(
+        **{
+            "inputTokens": 76,
+            "outputTokens": 259,
+            "totalTokens": 335,
+            "cacheWriteInputTokens": 362,
+            "cacheDetails": [
+                {"inputTokens": 74, "ttl": "1h"},
+                {"inputTokens": 288, "ttl": "5m"},
+            ],
+        }
+    )
+    config = AmazonConverseConfig()
+    openai_usage = config.transform_usage(usage)
+    details = openai_usage.prompt_tokens_details.cache_creation_token_details
+    assert details is not None
+    assert details.ephemeral_1h_input_tokens == 74
+    assert details.ephemeral_5m_input_tokens == 288
+
+
+def test_transform_usage_with_mismatched_cache_details_falls_back():
+    """An unrecognized ttl or partial breakdown must not silently understate
+    cache-write cost, so the split is only used when it fully accounts for
+    cacheWriteInputTokens."""
+    usage = ConverseTokenUsageBlock(
+        **{
+            "inputTokens": 76,
+            "outputTokens": 259,
+            "totalTokens": 335,
+            "cacheWriteInputTokens": 362,
+            "cacheDetails": [{"inputTokens": 74, "ttl": "1h"}],  # missing the 5m entry
+        }
+    )
+    config = AmazonConverseConfig()
+    openai_usage = config.transform_usage(usage)
+    assert (
+        getattr(openai_usage.prompt_tokens_details, "cache_creation_token_details", None)
+        is None
+    )
+
+
+def test_transform_usage_without_cache_details_stays_none():
+    """No cacheDetails in the response (older models/regions) should leave
+    cache_creation_token_details unset, same as before this field existed."""
+    usage = ConverseTokenUsageBlock(
+        **{
+            "inputTokens": 3,
+            "outputTokens": 401,
+            "totalTokens": 2193,
+            "cacheWriteInputTokens": 1789,
+        }
+    )
+    config = AmazonConverseConfig()
+    openai_usage = config.transform_usage(usage)
+    assert (
+        getattr(openai_usage.prompt_tokens_details, "cache_creation_token_details", None)
+        is None
+    )
+
+
+def test_bedrock_converse_1h_cache_write_billed_at_1h_rate(monkeypatch):
+    """Regression for issue #36760: without the cacheDetails split, the whole
+    write is billed at the (cheaper) 5m rate."""
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    usage = ConverseTokenUsageBlock(
+        **{
+            "inputTokens": 16,
+            "outputTokens": 4,
+            "totalTokens": 11652,
+            "cacheReadInputTokens": 0,
+            "cacheWriteInputTokens": 11632,
+            "cacheDetails": [{"inputTokens": 11632, "ttl": "1h"}],
+        }
+    )
+    openai_usage = AmazonConverseConfig().transform_usage(usage)
+    model = "bedrock/converse/global.anthropic.claude-opus-4-8"
+    prompt_cost, completion_cost = litellm.cost_calculator.cost_per_token(model=model, usage_object=openai_usage)
+    model_info = litellm.get_model_info(model=model)
+    expected_prompt_cost = (
+        16 * model_info["input_cost_per_token"] + 11632 * model_info["cache_creation_input_token_cost_above_1hr"]
+    )
+    assert prompt_cost == pytest.approx(expected_prompt_cost)
+    assert prompt_cost > 16 * model_info["input_cost_per_token"] + 11632 * model_info["cache_creation_input_token_cost"]
+    assert completion_cost == pytest.approx(4 * model_info["output_cost_per_token"])
+
+
 def test_transform_usage_with_reasoning_content():
     """Test that completion_tokens_details correctly tracks reasoning vs text tokens."""
     usage = ConverseTokenUsageBlock(