fix(model_prices): raise bedrock_mantle gpt-5.5 and gpt-5.4 max_input_tokens to Mantle's enforced 1050000

litellm/model_prices_and_context_window_backup.json

@@ -49605,7 +49605,7 @@
         "cache_read_input_token_cost": 5.5e-07,
         "output_cost_per_token": 3.3e-05,
         "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 272000,
+        "max_input_tokens": 1050000,
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "mode": "responses",
@@ -49632,7 +49632,7 @@
         "cache_read_input_token_cost": 2.75e-07,
         "output_cost_per_token": 1.65e-05,
         "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 272000,
+        "max_input_tokens": 1050000,
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "mode": "responses",

model_prices_and_context_window.json

@@ -49605,7 +49605,7 @@
         "cache_read_input_token_cost": 5.5e-07,
         "output_cost_per_token": 3.3e-05,
         "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 272000,
+        "max_input_tokens": 1050000,
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "mode": "responses",
@@ -49632,7 +49632,7 @@
         "cache_read_input_token_cost": 2.75e-07,
         "output_cost_per_token": 1.65e-05,
         "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 272000,
+        "max_input_tokens": 1050000,
         "max_output_tokens": 128000,
         "max_tokens": 128000,
         "mode": "responses",

tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py

@@ -531,6 +531,43 @@ def test_generic_cost_per_token_bedrock_mantle_gpt56_long_context(_local_model_c
     )
 
 
+@pytest.mark.parametrize(
+    "model",
+    [
+        "bedrock_mantle/openai.gpt-5.5",
+        "bedrock_mantle/openai.gpt-5.4",
+    ],
+)
+def test_generic_cost_per_token_bedrock_mantle_gpt55_gpt54_long_context_flat_rate(_local_model_cost_map, model):
+    """Bedrock serves gpt-5.5 and gpt-5.4 up to its enforced 1,050,000-token prompt maximum and documents
+    no long-context tier for them, so a prompt past 272K is billed at the flat per-token rates."""
+
+    model_cost_map = litellm.model_cost[model]
+    assert model_cost_map["max_input_tokens"] == 1050000
+    assert [key for key in model_cost_map if "above_272k" in key] == []
+
+    served_prompt_tokens = 1030590
+    cached_tokens = 100000
+    completion_tokens = 1000
+    usage = Usage(
+        prompt_tokens=served_prompt_tokens,
+        completion_tokens=completion_tokens,
+        total_tokens=served_prompt_tokens + completion_tokens,
+        prompt_tokens_details=PromptTokensDetailsWrapper(cached_tokens=cached_tokens),
+    )
+    prompt_cost, completion_cost = generic_cost_per_token(
+        model=model,
+        usage=usage,
+        custom_llm_provider="bedrock_mantle",
+    )
+    assert round(prompt_cost, 10) == round(
+        model_cost_map["input_cost_per_token"] * (served_prompt_tokens - cached_tokens)
+        + model_cost_map["cache_read_input_token_cost"] * cached_tokens,
+        10,
+    )
+    assert round(completion_cost, 10) == round(model_cost_map["output_cost_per_token"] * completion_tokens, 10)
+
+
 def test_generic_cost_per_token_honors_non_standard_above_threshold():
     """Regression for #30344: get_model_info must keep arbitrary
     input/output_cost_per_token_above_<N>_tokens thresholds, not only the hard-coded

tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py

@@ -1673,7 +1673,7 @@ class TestBedrockMantleResponsesPricing:
         assert info["input_cost_per_token"] == pytest.approx(5.5e-06)
         assert info["output_cost_per_token"] == pytest.approx(3.3e-05)
         assert info["cache_read_input_token_cost"] == pytest.approx(5.5e-07)
-        assert info["max_input_tokens"] == 272000
+        assert info["max_input_tokens"] == 1050000
 
     def test_gpt_5_4_pricing_and_mode(self, local_cost_map):
         info = litellm.get_model_info("bedrock_mantle/openai.gpt-5.4")
@@ -1681,7 +1681,7 @@ class TestBedrockMantleResponsesPricing:
         assert info["input_cost_per_token"] == pytest.approx(2.75e-06)
         assert info["output_cost_per_token"] == pytest.approx(1.65e-05)
         assert info["cache_read_input_token_cost"] == pytest.approx(2.75e-07)
-        assert info["max_input_tokens"] == 272000
+        assert info["max_input_tokens"] == 1050000
 
     @pytest.mark.parametrize(
         "model, input_cost, cache_creation_cost, cache_read_cost, output_cost",
@@ -1753,13 +1753,14 @@ def _repo_cost_map(map_name: str) -> dict[str, dict[str, object]]:
     return json.loads(paths[map_name].read_text())
 
 
-class TestGpt56MantleRegistryEntries:
-    """Locks the gpt-5.6 frontier entries to Bedrock Mantle's live behavior.
+class TestMantleGptRegistryEntries:
+    """Locks the OpenAI GPT entries to Bedrock Mantle's live behavior.
 
     Mantle enforces a 1,050,000-token prompt maximum for gpt-5.6 sol/terra/luna
-    (oversize requests 400 with "prompt tokens (N) exceed model maximum
-    (1050000)", and a 1,030,590-token request completes), matching the OpenAI
-    Bedrock guide. mode must stay "responses": Mantle's native
+    and for gpt-5.5 and gpt-5.4 (oversize requests 400 with "prompt tokens (N)
+    exceed model maximum (1050000)", and a 1,030,590-token request completes
+    on every one of them), while the AWS model cards still quote 272K for
+    gpt-5.5 and gpt-5.4. mode must stay "responses": Mantle's native
     /v1/chat/completions rejects function tools unless reasoning_effort is
     "none", so chat traffic has to keep bridging to the Responses API
     (see the responses_api_bridge tests above).
@@ -1781,3 +1782,18 @@ class TestGpt56MantleRegistryEntries:
         assert entry["mode"] == "responses"
         assert entry["use_openai_responses_path"] is True
         assert entry["supported_endpoints"] == ["/v1/chat/completions", "/v1/responses"]
+
+    @pytest.mark.parametrize("map_name", ("root", "bundled_backup"))
+    @pytest.mark.parametrize(
+        "key",
+        (
+            "bedrock_mantle/openai.gpt-5.5",
+            "bedrock_mantle/openai.gpt-5.4",
+        ),
+    )
+    def test_gpt_55_and_54_entries_match_mantle_enforced_limits(self, map_name, key):
+        entry = _repo_cost_map(map_name)[key]
+        assert entry["max_input_tokens"] == 1050000
+        assert entry["max_output_tokens"] == 128000
+        assert entry["mode"] == "responses"
+        assert entry["use_openai_responses_path"] is True