fix(cost): recognize character rates in deployment cost-map selection

A deployment whose only rates are input_cost_per_character /
output_cost_per_character (e.g. a custom OpenAI-compatible TTS backend)
failed _cost_map_entry_prices_anything(): the character fields are
neither in _NON_TOKEN_RATE_FIELDS nor token-named, so the
"prices anything" check returned False. With custom_pricing=True the
router_model_id was then never selected and audio_speech (aspeech)
resolved its price through the bare model name — which is not in the
cost map — producing spend = 0 and no x-litellm-response-cost header
(issue #44200).

Add both character fields to _NON_TOKEN_RATE_FIELDS so character-only
deployments are selected like per-second and per-query deployments.

litellm/cost_calculator.py

@@ -800,7 +800,15 @@ def _get_hidden_str_for_cost_calc(hidden_params: object, key: str) -> str | None
 
 
 _NON_TOKEN_RATE_FIELDS: Final = frozenset(
-    {"cost_per_second", "input_cost_per_second", "output_cost_per_second", "input_cost_per_query", "tiered_pricing"}
+    {
+        "cost_per_second",
+        "input_cost_per_second",
+        "output_cost_per_second",
+        "input_cost_per_query",
+        "input_cost_per_character",
+        "output_cost_per_character",
+        "tiered_pricing",
+    }
 )
 
 

tests/unit/test_cost_calculator.py

@@ -186,7 +186,9 @@ def test_response_cost_calculator_keeps_optional_params_out_of_hidden_params():
     assert optional_params["aws_session_token"] == "session-secret"
 
 
-def test_embedding_success_logging_and_spend_log_carry_no_forwarded_credentials(monkeypatch: pytest.MonkeyPatch) -> None:
+def test_embedding_success_logging_and_spend_log_carry_no_forwarded_credentials(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
     from litellm.proxy import proxy_server
     from litellm.proxy.spend_tracking.spend_tracking_utils import _get_proxy_server_request_for_spend_logs_payload
 
@@ -235,10 +237,6 @@ def test_embedding_success_logging_and_spend_log_carry_no_forwarded_credentials(
     assert logging_obj.optional_params["extra_headers"] == {"x-goog-api-key": "goog-secret"}
 
 
-
-
-
-
 def test_realtime_stream_combines_text_and_audio_token_details():
     """Realtime response.done usage with input_token_details / output_token_details."""
     from litellm.cost_calculator import RealtimeAPITokenUsageProcessor
@@ -1353,8 +1351,6 @@ def test_bedrock_cost_calculator_comparison_with_without_cache():
     print(f"Cost with cache: {cost_with_cache}")
 
 
-
-
 def test_gemini_25_explicit_caching_cost_direct_usage():
     """
     Test that Gemini 2.5 models correctly calculate costs with explicit caching.
@@ -1923,8 +1919,6 @@ def test_cost_margin_with_discount(monkeypatch):
     print(f"  - Expected: ${expected_cost:.6f}")
 
 
-
-
 def test_completion_cost_extracts_service_tier_from_response(_local_model_cost_map):
     """Test that completion_cost extracts service_tier from completion_response object."""
     from litellm import completion_cost
@@ -2674,8 +2668,6 @@ def test_gemini_without_cache_tokens_details():
     print("✅ Gemini without cacheTokensDetails works correctly")
 
 
-
-
 def test_additional_costs_only_for_azure_ai(_local_model_cost_map):
     """
     Test that _get_additional_costs is only called for azure_ai provider.
@@ -3220,9 +3212,7 @@ def test_cost_per_token_resolves_per_second_rate_precedence(
 
     model: Final = "test-chat-per-second-rate-precedence"
     entry: Final = {**pricing_fields, "litellm_provider": "together_ai", "mode": "chat"}
-    litellm.register_model(
-        model_cost={model: entry}
-    )
+    litellm.register_model(model_cost={model: entry})
 
     assert cost_per_token(
         model=model,
@@ -3647,6 +3637,42 @@ def test_combine_usage_objects_sums_mirrored_cache_write_fields_once():
     assert combined_pair.prompt_tokens_details.cache_creation_tokens == 100
 
 
+def test_select_model_name_selects_character_priced_deployment(_local_model_cost_map):
+    """
+    A deployment whose only rate is input_cost_per_character must be selected
+    by router_model_id: the aspeech cost path resolves its price through the
+    deployment entry, and a character-only entry failing the "prices anything"
+    check silently produced spend = 0 (issue #44200).
+    """
+    from litellm.cost_calculator import _select_model_name_for_cost_calc
+
+    router_model_id = "openai/qwen-audio-3.1-tts-flash-uuid"
+    litellm.model_cost[router_model_id] = {
+        "input_cost_per_character": 1e-8,
+        "output_cost_per_character": 0.0,
+        "litellm_provider": "openai",
+    }
+
+    selected = _select_model_name_for_cost_calc(
+        model="qwen-audio-3.1-tts-flash",
+        completion_response=None,
+        custom_pricing=True,
+        custom_llm_provider="openai",
+        router_model_id=router_model_id,
+    )
+
+    assert selected == router_model_id
+
+
+def test_cost_map_entry_prices_anything_recognizes_character_rates():
+    from litellm.cost_calculator import _cost_map_entry_prices_anything
+
+    assert _cost_map_entry_prices_anything({"input_cost_per_character": 1e-8}) is True
+    assert _cost_map_entry_prices_anything({"output_cost_per_character": 0.0}) is True
+    assert _cost_map_entry_prices_anything({"input_cost_per_token": 1e-6}) is True
+    assert _cost_map_entry_prices_anything({"mode": "audio_speech"}) is False
+
+
 def test_select_model_name_strips_unregistered_alias_prefix(_local_model_cost_map):
     """A router-facing model_name alias containing "/" whose leading segment is NOT a
     registered provider must not be double-prefixed into a non-existent cost key.
@@ -4785,9 +4811,7 @@ def test_xai_batch_tier_discounts_the_long_context_rate_like_the_flat_batch_rate
         assert info[f"{prefix}_above_200k_tokens_batches"] < info[f"{prefix}_above_200k_tokens"]
 
 
-@pytest.mark.parametrize(
-    ("prompt_tokens", "tier"), [(200_000, "_above_200k_tokens_batches"), (199_999, "_batches")]
-)
+@pytest.mark.parametrize(("prompt_tokens", "tier"), [(200_000, "_above_200k_tokens_batches"), (199_999, "_batches")])
 def test_xai_batch_cost_calculator_bills_the_200k_batch_tier_inclusively(
     _local_model_cost_map: None, prompt_tokens: int, tier: str
 ) -> None: