diff --git a/litellm/constants.py b/litellm/constants.py
index e07d727973d..cfee777f36a 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -7,6 +7,7 @@ from typing import Final, Literal
 
 from litellm.litellm_core_utils.env_utils import (
     get_env_float,
+    get_env_float_in_range,
     get_env_float_or_none,
     get_env_int,
     get_env_int_in_range,
@@ -149,6 +150,9 @@ DEFAULT_FAILURE_THRESHOLD_PERCENT: Final = get_env_float(
     "DEFAULT_FAILURE_THRESHOLD_PERCENT", 0.5
 )  # default cooldown a deployment if 50% of requests fail in a given minute
 DEFAULT_MAX_TOKENS: Final = get_env_int("DEFAULT_MAX_TOKENS", 4096)
+NO_MAX_TOKENS_TPM_RESERVATION_FRACTION: Final = get_env_float_in_range(
+    "NO_MAX_TOKENS_TPM_RESERVATION_FRACTION", 0.25, 0.01, 1.0
+)
 DEFAULT_ALLOWED_FAILS: Final = get_env_int("DEFAULT_ALLOWED_FAILS", 3)
 DEFAULT_REDIS_SYNC_INTERVAL: Final = get_env_int("DEFAULT_REDIS_SYNC_INTERVAL", 1)
 DEFAULT_COOLDOWN_TIME_SECONDS: Final = get_env_int("DEFAULT_COOLDOWN_TIME_SECONDS", 5)
diff --git a/litellm/litellm_core_utils/env_utils.py b/litellm/litellm_core_utils/env_utils.py
index 6883af98bbd..462b0b3df47 100644
--- a/litellm/litellm_core_utils/env_utils.py
+++ b/litellm/litellm_core_utils/env_utils.py
@@ -71,7 +71,15 @@ def get_env_int_in_range(env_var: str, default: int, minimum: int, maximum: int)
     Values outside the range fall back to the default and warn, so a misconfigured knob can
     neither crash the caller nor silently change the meaning of what it computes.
     """
-    value: Final = get_env_int(env_var, default)
+    return _within_range(env_var, get_env_int(env_var, default), default, minimum, maximum)
+
+
+def get_env_float_in_range(env_var: str, default: float, minimum: float, maximum: float) -> float:
+    """Float counterpart of `get_env_int_in_range`."""
+    return _within_range(env_var, get_env_float(env_var, default), default, minimum, maximum)
+
+
+def _within_range(env_var: str, value: _NumberT, default: _NumberT, minimum: _NumberT, maximum: _NumberT) -> _NumberT:
     if minimum <= value <= maximum:
         return value
     logging.getLogger("LiteLLM").warning(
diff --git a/litellm/proxy/hooks/parallel_request_limiter_v3.py b/litellm/proxy/hooks/parallel_request_limiter_v3.py
index 404aff84994..14b08a09116 100644
--- a/litellm/proxy/hooks/parallel_request_limiter_v3.py
+++ b/litellm/proxy/hooks/parallel_request_limiter_v3.py
@@ -42,7 +42,11 @@ from litellm.caching.redis_batch import (
     active_request_redis_batch,
 )
 from litellm.caching.redis_cache import log_redis_failure
-from litellm.constants import DYNAMIC_RATE_LIMIT_ERROR_THRESHOLD_PER_MINUTE, INTERNAL_CALL_ORIGIN_METADATA_KEY
+from litellm.constants import (
+    DYNAMIC_RATE_LIMIT_ERROR_THRESHOLD_PER_MINUTE,
+    INTERNAL_CALL_ORIGIN_METADATA_KEY,
+    NO_MAX_TOKENS_TPM_RESERVATION_FRACTION,
+)
 from litellm.cost_calculator import get_usage_object
 from litellm.integrations.custom_logger import CustomLogger
 from litellm.litellm_core_utils.audio_utils.utils import estimate_audio_tokens
@@ -508,11 +512,6 @@ REDIS_NODE_HASHTAG_NAME: Final = "all_keys"
 # *some* output budget; these define that fallback estimate.
 DEFAULT_MAX_TOKENS_ESTIMATE: Final = 4096
 DEFAULT_CHARS_PER_TOKEN: Final = 4
-# Fraction of the available output budget reserved as the upfront floor when
-# the request omits max_tokens. Applied to both DEFAULT_MAX_TOKENS_ESTIMATE
-# (baseline floor) and to the smallest configured TPM limit (capped floor for
-# small per-tenant TPM caps).
-_TPM_FLOOR_FRACTION: Final = 4
 # Both embeddings and the Responses API put their prompt in data["input"],
 # but only embeddings have no output tokens. Every "is this an embedding"
 # check on data["input"] must exclude these call types, or a Responses call
@@ -1003,10 +1002,10 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger):
         per-tenant cap can't be tripped by the floor alone. Returns the
         baseline floor when no limit is provided.
         """
-        baseline: Final = DEFAULT_MAX_TOKENS_ESTIMATE // _TPM_FLOOR_FRACTION
+        baseline: Final = int(DEFAULT_MAX_TOKENS_ESTIMATE * NO_MAX_TOKENS_TPM_RESERVATION_FRACTION)
         if min_configured_tpm_limit is None:
             return baseline
-        return min(baseline, max(1, min_configured_tpm_limit // _TPM_FLOOR_FRACTION))
+        return min(baseline, max(1, int(min_configured_tpm_limit * NO_MAX_TOKENS_TPM_RESERVATION_FRACTION)))
 
     @staticmethod
     def _is_embedding_request(data: object, call_type: str | None) -> bool:
@@ -1138,7 +1137,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger):
             if call_type in RESPONSES_API_CALL_TYPES
             else base_capped_floor
         )
-        baseline_floor: Final = DEFAULT_MAX_TOKENS_ESTIMATE // _TPM_FLOOR_FRACTION
+        baseline_floor: Final = int(DEFAULT_MAX_TOKENS_ESTIMATE * NO_MAX_TOKENS_TPM_RESERVATION_FRACTION)
         is_embedding: Final = PROXY_MaxParallelRequestsHandler_v3._is_embedding_request(data, call_type)
         if (
             capped_floor >= baseline_floor
diff --git a/litellm/router.py b/litellm/router.py
index 3a423b79e49..20af2e5649e 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -377,6 +377,7 @@ from litellm.router_utils.pre_call_checks.encrypted_content_affinity_check impor
     EncryptedContentAffinityCheck,
 )
 from litellm.router_utils.pre_call_checks.io_token_rate_limit_check import (
+    async_io_token_refund_failure,
     build_io_token_rate_limit_headers,
     deployment_has_io_token_limits,
     refund_stale_reservation_before_retry,
@@ -9500,7 +9501,7 @@ class Router(DeprecatedRouterMembers):
 
             raise original_exception
 
-    async def make_call(self, original_function: Any, *args, **kwargs):
+    async def make_call(self, original_function: Any, *args: object, **kwargs: object):
         """
         Handler for making a call to the .completion()/.embeddings()/etc. functions.
         """
@@ -9509,17 +9510,26 @@ class Router(DeprecatedRouterMembers):
         endpoint_function: Final = (
             generic_function if callable(generic_function) else _OPAQUE_VALUE_ADAPTER.validate_python(original_function)
         )
-        with endpoint_selection(
-            getattr(endpoint_function, "__name__", None),
-            getattr(endpoint_function, "__module__", None),
-            model=_OPAQUE_VALUE_ADAPTER.validate_python(model_group),
-        ):
-            response = original_function(*args, **kwargs)
-            if coroutine_checker.is_async_callable(response) or inspect.isawaitable(response):
-                response = await response
+        try:
+            with endpoint_selection(
+                getattr(endpoint_function, "__name__", None),
+                getattr(endpoint_function, "__module__", None),
+                model=_OPAQUE_VALUE_ADAPTER.validate_python(model_group),
+            ):
+                response = original_function(*args, **kwargs)
+                if coroutine_checker.is_async_callable(response) or inspect.isawaitable(response):
+                    response = await response
+        except Exception:
+            with contextlib.suppress(Exception):
+                await async_io_token_refund_failure(
+                    self.cache, kwargs, parent_otel_span=get_parent_otel_span_from_kwargs(kwargs)
+                )
+            raise
         await self.increment_deployment_usage_for_response(response=response, request_kwargs=kwargs)
         ## PROCESS RESPONSE HEADERS
-        response = await self.set_response_headers(response=response, model_group=model_group, request_kwargs=kwargs)
+        response = await self.set_response_headers(
+            response=response, model_group=model_group if isinstance(model_group, str) else None, request_kwargs=kwargs
+        )
 
         return response
 
diff --git a/litellm/router_utils/pre_call_checks/io_token_rate_limit_check.py b/litellm/router_utils/pre_call_checks/io_token_rate_limit_check.py
index 0b3d48c9e1d..7580c7dadd3 100644
--- a/litellm/router_utils/pre_call_checks/io_token_rate_limit_check.py
+++ b/litellm/router_utils/pre_call_checks/io_token_rate_limit_check.py
@@ -1,7 +1,8 @@
 """
 Separate ITPM/OTPM (input/output tokens per minute) deployment rate limits.
 
-- Pre-call: atomically reserve estimated_input against ITPM and max_tokens against OTPM
+- Pre-call: atomically reserve estimated_input against ITPM and max_tokens against OTPM; a request
+  without max_tokens reserves the model's max output, capped at a fraction of the OTPM limit
 - Post-call: reconcile ITPM to actual input tokens and OTPM to actual output tokens
 - Cached prompt-read tokens are excluded from ITPM post-call accounting
 
@@ -22,6 +23,7 @@ from litellm import token_counter
 from litellm._internal_context import with_service_target
 from litellm._logging import verbose_router_logger
 from litellm.caching.dual_cache import DualCache
+from litellm.constants import NO_MAX_TOKENS_TPM_RESERVATION_FRACTION
 from litellm.litellm_core_utils.token_counter import deployment_openai_model, offload_token_count
 from litellm.llms.azure.ptu_capacity import is_str_keyed_mapping
 from litellm.router_utils.routing_read_batch import ROUTER_USAGE_TARGET
@@ -127,10 +129,15 @@ def _get_cache_keys(deployment: dict, current_minute: str) -> tuple[str, str] |
     return itpm_key, otpm_key
 
 
-def _tokenizer_model(deployment: object) -> str:
+def _served_model(deployment: object) -> str:
     params: Final = deployment.get("litellm_params") if is_str_keyed_mapping(deployment) else None
     served: Final = params.get("model") if is_str_keyed_mapping(params) else None
-    return deployment_openai_model(deployment) or (served if isinstance(served, str) else "")
+    return served if isinstance(served, str) else ""
+
+
+def _tokenizer_and_served_models(deployment: object) -> tuple[str, str]:
+    served: Final = _served_model(deployment)
+    return deployment_openai_model(deployment) or served, served
 
 
 def _estimate_input_tokens(request_kwargs: dict[str, Any] | None, model: str = "") -> int:
@@ -160,24 +167,61 @@ def _model_max_output_tokens(model_name: str) -> int | None:
     return None
 
 
-def _resolve_max_tokens(request_kwargs: dict[str, Any] | None, deployment: dict) -> int:
-    if request_kwargs:
-        # An explicit max_tokens=0 must be honored, not treated as absent and
-        # replaced by the model default.
-        explicit = request_kwargs.get("max_tokens")
-        if explicit is None:
-            explicit = request_kwargs.get("max_completion_tokens")
-        if explicit is None:
-            explicit = request_kwargs.get("max_output_tokens")
-        if explicit is not None:
-            return max(0, int(explicit))
+_CHAT_OUTPUT_CAP_KEYS: Final = ("max_tokens", "max_completion_tokens")
+_RESPONSES_OUTPUT_CAP_KEYS: Final = ("max_output_tokens",)
+_OUTPUT_CAP_KEYS: Final = _CHAT_OUTPUT_CAP_KEYS + _RESPONSES_OUTPUT_CAP_KEYS
 
-    model_name: Final = (deployment.get("litellm_params") or {}).get("model")
-    if model_name:
-        model_max: Final = _model_max_output_tokens(model_name)
-        if model_max is not None:
-            return model_max
-    return 4096
+
+def _explicit_max_tokens(
+    request_kwargs: Mapping[str, object] | None, cap_keys: tuple[str, ...] = _OUTPUT_CAP_KEYS
+) -> int | None:
+    if not request_kwargs:
+        return None
+    explicit: Final = next(
+        (request_kwargs[key] for key in cap_keys if request_kwargs.get(key) is not None),
+        None,
+    )
+    match explicit:
+        case int() | float() | str():
+            return max(0, int(explicit))
+        case _:
+            return None
+
+
+def _sent_deployment_cap_keys(request_kwargs: Mapping[str, object] | None) -> tuple[str, ...]:
+    is_responses_request: Final = (
+        request_kwargs is not None and "input" in request_kwargs and "messages" not in request_kwargs
+    )
+    return _RESPONSES_OUTPUT_CAP_KEYS if is_responses_request else _CHAT_OUTPUT_CAP_KEYS
+
+
+def _deployment_output_cap(request_kwargs: Mapping[str, object] | None, deployment: Mapping[str, object]) -> int | None:
+    params: Final = deployment.get("litellm_params")
+    return (
+        _explicit_max_tokens(params, _sent_deployment_cap_keys(request_kwargs))
+        if is_str_keyed_mapping(params)
+        else None
+    )
+
+
+def _default_otpm_reservation(model_name: str, otpm_limit: int) -> int:
+    model_max: Final = _model_max_output_tokens(model_name) if model_name else None
+    share_of_limit: Final = max(1, int(otpm_limit * NO_MAX_TOKENS_TPM_RESERVATION_FRACTION))
+    return min(4096 if model_max is None else model_max, share_of_limit)
+
+
+def _otpm_reservation(
+    request_kwargs: Mapping[str, object] | None,
+    deployment: Mapping[str, object],
+    model_name: str,
+    otpm_limit: int,
+) -> int:
+    from_request: Final = _explicit_max_tokens(request_kwargs)
+    if from_request is not None:
+        return from_request
+    default: Final = _default_otpm_reservation(model_name, otpm_limit)
+    from_deployment: Final = _deployment_output_cap(request_kwargs, deployment)
+    return default if from_deployment is None else min(from_deployment, default)
 
 
 def _get_usage_tokens(usage: object) -> tuple[int, int, int]:
@@ -210,6 +254,12 @@ def _extract_response_usage(response_obj: object) -> object:
     return getattr(response_obj, "usage", None)
 
 
+def _openai_shaped_usage(usage: object) -> object:
+    if isinstance(usage, dict) and litellm.AnthropicConfig.is_anthropic_usage_object(usage):
+        return litellm.AnthropicConfig().calculate_usage(usage_object=usage, reasoning_content=None)
+    return usage
+
+
 def _usage_is_present(usage: object) -> bool:
     """
     True only if usage carries an actual input/output breakdown.
@@ -238,7 +288,7 @@ def _resolve_reconcile_usage_tokens(
     fields. When usage cannot be resolved, return ``usage_resolved=False`` so
     callers keep the pre-call reservation instead of refunding it as zero usage.
     """
-    usage: Final = _extract_response_usage(response_obj)
+    usage: Final = _openai_shaped_usage(_extract_response_usage(response_obj))
     if _usage_is_present(usage):
         prompt_tokens, completion_tokens, cached_tokens = _get_usage_tokens(usage)
         return max(0, prompt_tokens - cached_tokens), completion_tokens, True
@@ -261,6 +311,21 @@ def _resolve_reconcile_usage_tokens(
     return 0, 0, False
 
 
+def _key_for_this_minute(reserved_key: str) -> str:
+    counter, _, _ = reserved_key.rpartition(":")
+    return f"{counter}:{get_utc_datetime().strftime('%H-%M')}"
+
+
+def _reconcile_increments(
+    reservation: tuple[int, int, str | None, str | None], billable_input: int, completion_tokens: int
+) -> tuple[tuple[str, int], ...]:
+    itpm_reserved, otpm_reserved, itpm_key, otpm_key = reservation
+    deltas: Final = ((itpm_key, billable_input - itpm_reserved), (otpm_key, completion_tokens - otpm_reserved))
+    return tuple(
+        (key if delta < 0 else _key_for_this_minute(key), delta) for key, delta in deltas if key is not None and delta
+    )
+
+
 def _stash_reservation_in_metadata(
     request_kwargs: dict[str, object] | None,
     *,
@@ -311,7 +376,9 @@ def _reservation_channels(kwargs: Mapping[str, object] | None) -> tuple[object,
         return ()
     top_level: Final = (kwargs.get("metadata"), kwargs.get("litellm_metadata"))
     litellm_params: Final = _as_mutable_mapping(kwargs.get("litellm_params"))
-    from_params: Final = () if litellm_params is None else (litellm_params.get("metadata"),)
+    from_params: Final = (
+        () if litellm_params is None else (litellm_params.get("metadata"), litellm_params.get("litellm_metadata"))
+    )
     standard_logging_object: Final = _as_mutable_mapping(kwargs.get("standard_logging_object"))
     from_logging_object: Final = () if standard_logging_object is None else (standard_logging_object.get("metadata"),)
     return top_level + from_params + from_logging_object
@@ -433,9 +500,11 @@ def io_token_pre_call_check(
         return deployment
 
     request_kwargs: Final = get_io_token_rate_limit_request_kwargs()
-    _model: Final = _tokenizer_model(deployment)
+    _model, served_model = _tokenizer_and_served_models(deployment)
     estimated_input: Final = _estimate_input_tokens(request_kwargs, model=_model)
-    max_tokens: Final = _resolve_max_tokens(request_kwargs, deployment)
+    otpm_to_reserve: Final = (
+        _otpm_reservation(request_kwargs, deployment, served_model, otpm_limit) if otpm_limit is not None else 0
+    )
 
     dt: Final = get_utc_datetime()
     current_minute: Final = dt.strftime("%H-%M")
@@ -458,7 +527,7 @@ def io_token_pre_call_check(
         )
 
     if otpm_limit is not None:
-        otpm_reserved = 0 if max_tokens == 0 else _reservation_value(max_tokens, otpm_limit)
+        otpm_reserved = otpm_to_reserve
         try:
             _sync_increment_with_rollback(
                 dual_cache,
@@ -497,9 +566,11 @@ async def async_io_token_pre_call_check(
         return deployment
 
     request_kwargs: Final = get_io_token_rate_limit_request_kwargs()
-    _model: Final = _tokenizer_model(deployment)
+    _model, served_model = _tokenizer_and_served_models(deployment)
     estimated_input: Final = await offload_token_count(_estimate_input_tokens)(request_kwargs, model=_model)
-    max_tokens: Final = _resolve_max_tokens(request_kwargs, deployment)
+    otpm_to_reserve: Final = (
+        _otpm_reservation(request_kwargs, deployment, served_model, otpm_limit) if otpm_limit is not None else 0
+    )
 
     dt: Final = get_utc_datetime()
     current_minute: Final = dt.strftime("%H-%M")
@@ -523,7 +594,7 @@ async def async_io_token_pre_call_check(
         )
 
     if otpm_limit is not None:
-        otpm_reserved = 0 if max_tokens == 0 else _reservation_value(max_tokens, otpm_limit)
+        otpm_reserved = otpm_to_reserve
         try:
             await _increment_with_rollback(
                 dual_cache,
@@ -564,7 +635,8 @@ def io_token_reconcile_success(
 ) -> None:
     request_kwargs: Final[Mapping[str, object] | None] = kwargs
     response: Final[object] = response_obj
-    itpm_reserved, otpm_reserved, itpm_key, otpm_key = _read_reservation_from_kwargs(request_kwargs)
+    reservation: Final = _read_reservation_from_kwargs(request_kwargs)
+    itpm_reserved, otpm_reserved, itpm_key, otpm_key = reservation
     if itpm_key is None and otpm_key is None:
         return
 
@@ -572,23 +644,8 @@ def io_token_reconcile_success(
 
     try:
         if usage_resolved:
-            if itpm_key is not None:
-                itpm_delta: Final = billable_input - itpm_reserved
-                if itpm_delta != 0:
-                    dual_cache.increment_cache(
-                        key=itpm_key,
-                        value=itpm_delta,
-                        ttl=RoutingArgsTTL,
-                    )
-
-            if otpm_key is not None:
-                otpm_delta: Final = completion_tokens - otpm_reserved
-                if otpm_delta != 0:
-                    dual_cache.increment_cache(
-                        key=otpm_key,
-                        value=otpm_delta,
-                        ttl=RoutingArgsTTL,
-                    )
+            for key, delta in _reconcile_increments(reservation, billable_input, completion_tokens):
+                dual_cache.increment_cache(key=key, value=delta, ttl=RoutingArgsTTL)
         else:
             verbose_router_logger.debug(
                 "[IO TOKEN LIMIT] usage missing; keeping reservation (itpm_reserved=%s, otpm_reserved=%s)",
@@ -618,39 +675,23 @@ async def async_io_token_reconcile_success(
 ) -> None:
     request_kwargs: Final[Mapping[str, object] | None] = kwargs
     response: Final[object] = response_obj
-    itpm_reserved, otpm_reserved, itpm_key, otpm_key = _read_reservation_from_kwargs(request_kwargs)
+    reservation: Final = _read_reservation_from_kwargs(request_kwargs)
+    itpm_reserved, otpm_reserved, itpm_key, otpm_key = reservation
     if itpm_key is None and otpm_key is None:
         return
 
     billable_input, completion_tokens, usage_resolved = _resolve_reconcile_usage_tokens(request_kwargs, response)
 
-    # Reconcile against the exact key that held the reservation (which encodes
-    # the reservation's minute), not a key recomputed at response time. This
-    # tracks actual usage even when the pre-call estimate was 0, and avoids a
-    # minute-boundary mismatch for calls that span into the next minute. Always
-    # clear the stash afterwards (even if an increment throws) so a retry or a
-    # duplicate success event can't re-process it.
+    # A refund goes back to the minute that held the reservation, while usage above the reservation is charged
+    # to the minute the response finished in, so a call that runs past its minute still counts against a live
+    # window. Always clear the stash afterwards (even if an increment throws) so a retry or a duplicate success
+    # event can't re-process it.
     try:
         if usage_resolved:
-            if itpm_key is not None:
-                itpm_delta: Final = billable_input - itpm_reserved
-                if itpm_delta != 0:
-                    await dual_cache.async_increment_cache(
-                        key=itpm_key,
-                        value=itpm_delta,
-                        ttl=RoutingArgsTTL,
-                        parent_otel_span=parent_otel_span,
-                    )
-
-            if otpm_key is not None:
-                otpm_delta: Final = completion_tokens - otpm_reserved
-                if otpm_delta != 0:
-                    await dual_cache.async_increment_cache(
-                        key=otpm_key,
-                        value=otpm_delta,
-                        ttl=RoutingArgsTTL,
-                        parent_otel_span=parent_otel_span,
-                    )
+            for key, delta in _reconcile_increments(reservation, billable_input, completion_tokens):
+                await dual_cache.async_increment_cache(
+                    key=key, value=delta, ttl=RoutingArgsTTL, parent_otel_span=parent_otel_span
+                )
         else:
             verbose_router_logger.debug(
                 "[IO TOKEN LIMIT] usage missing; keeping reservation (itpm_reserved=%s, otpm_reserved=%s)",
diff --git a/litellm/router_utils/pre_call_checks/model_rate_limit_check.py b/litellm/router_utils/pre_call_checks/model_rate_limit_check.py
index f4b41211c6e..f41d19cd62c 100644
--- a/litellm/router_utils/pre_call_checks/model_rate_limit_check.py
+++ b/litellm/router_utils/pre_call_checks/model_rate_limit_check.py
@@ -26,7 +26,6 @@ from litellm.caching.dual_cache import DualCache
 from litellm.caching.redis_cache import RedisCircuitBreakerOpenError
 from litellm.integrations.custom_logger import CustomLogger
 from litellm.router_utils.pre_call_checks.io_token_rate_limit_check import (
-    ITPM_RESERVED_KEY,
     async_io_token_pre_call_check,
     async_io_token_reconcile_success,
     async_io_token_refund_failure,
@@ -485,24 +484,12 @@ class ModelRateLimitingCheck(CustomLogger):
 
         try:
             standard_logging_object: Final[StandardLoggingPayload | None] = kwargs.get("standard_logging_object")
-
-            # IO token reconciliation works purely from the cache keys stashed in
-            # kwargs/metadata, so it must run before the model_id guard below
-            # (which only the TPM-tracking path needs). Otherwise a request whose
-            # standard_logging_object lacks model_id would never return its
-            # reservation, leaving the counter elevated until the TTL expires.
-            slo_metadata: Final = (standard_logging_object.get("metadata") or {}) if standard_logging_object else {}
-            kwargs_metadata: Final = kwargs.get("metadata") or {}
-            if ITPM_RESERVED_KEY in slo_metadata or ITPM_RESERVED_KEY in kwargs_metadata:
-                await async_io_token_reconcile_success(
-                    self.dual_cache,
-                    kwargs,
-                    response_obj,
-                    parent_otel_span=get_parent_otel_span_from_kwargs(kwargs),
-                )
-                # Fall through: a deployment can also configure tpm/rpm alongside
-                # itpm/otpm, and that path's pre-call check reads the tpm_key
-                # counter tracked below, so it must still be incremented here.
+            await async_io_token_reconcile_success(
+                self.dual_cache,
+                kwargs,
+                response_obj,
+                parent_otel_span=get_parent_otel_span_from_kwargs(kwargs),
+            )
 
             if standard_logging_object is None:
                 return
@@ -557,17 +544,7 @@ class ModelRateLimitingCheck(CustomLogger):
         """
         try:
             standard_logging_object: Final[StandardLoggingPayload | None] = kwargs.get("standard_logging_object")
-            slo_metadata: Final = (standard_logging_object.get("metadata") or {}) if standard_logging_object else {}
-            kwargs_metadata: Final = kwargs.get("metadata") or {}
-            if ITPM_RESERVED_KEY in slo_metadata or ITPM_RESERVED_KEY in kwargs_metadata:
-                io_token_reconcile_success(
-                    self.dual_cache,
-                    kwargs,
-                    response_obj,
-                )
-                # Fall through: a deployment can also configure tpm/rpm alongside
-                # itpm/otpm, and that path's pre-call check reads the tpm_key
-                # counter tracked below, so it must still be incremented here.
+            io_token_reconcile_success(self.dual_cache, kwargs, response_obj)
 
             if standard_logging_object is None:
                 return
diff --git a/tests/integration/routing/test_otpm_default_reservation_fraction.py b/tests/integration/routing/test_otpm_default_reservation_fraction.py
new file mode 100644
index 00000000000..589a2535a03
--- /dev/null
+++ b/tests/integration/routing/test_otpm_default_reservation_fraction.py
@@ -0,0 +1,137 @@
+from __future__ import annotations
+
+import dataclasses
+import threading
+import uuid
+from collections.abc import Callable, Iterator
+from concurrent.futures import ThreadPoolExecutor
+from dataclasses import dataclass
+from datetime import UTC, datetime
+from pathlib import Path
+from queue import SimpleQueue
+from typing import Final
+
+import httpx
+import pytest
+from integration._support.client import JSON_OBJECT, gateway_from_environment
+from integration._support.openai_wire import chat_reply
+from integration._support.process import OwnedProxy, graceful_stop_seconds, owned_proxy_process
+from integration._support.wire import Reply, Request, Wire, wire_server
+from integration.providers._cache_control_marks_support import owned_config
+from integration.routing.test_payment_required_mapping import OPENAI_MODEL, is_model_info_probe, model_list_reply
+
+pytestmark: Final = pytest.mark.timeout(2 * graceful_stop_seconds() + 120)
+
+GROUPS: Final = ("otpm-fraction-first", "otpm-fraction-retry")
+OTPM_LIMIT: Final = 1000
+FRACTION: Final = 0.5
+DEFAULT_RESERVATION: Final = int(OTPM_LIMIT * FRACTION)
+
+
+@dataclass(frozen=True, slots=True)
+class Rig:
+    owned: OwnedProxy
+    upstream: Wire
+    gates: SimpleQueue[threading.Event]
+
+
+@dataclass(frozen=True, slots=True)
+class Admissions:
+    held_forwarded_max_tokens: bool
+    statuses: tuple[int, int, int]
+    one_minute: bool
+
+
+def _reply_for(gates: SimpleQueue[threading.Event]) -> Callable[[Request], Reply]:
+    def reply(request: Request) -> Reply:
+        if is_model_info_probe(request):
+            return model_list_reply()
+        if JSON_OBJECT.validate_json(request.body).get("stream") is True:
+            return dataclasses.replace(
+                chat_reply("chatcmpl-held", OPENAI_MODEL, "held", stream=True), gate_before_first=gates.get(timeout=60)
+            )
+        return chat_reply("chatcmpl-capped", OPENAI_MODEL, "capped", stream=False)
+
+    return reply
+
+
+def _config(directory: Path, upstream: Wire) -> Path:
+    return owned_config(
+        directory,
+        [
+            {
+                "model_name": group,
+                "litellm_params": {
+                    "model": OPENAI_MODEL,
+                    "api_base": upstream.url + "/v1",
+                    "api_key": "synthetic-openai-key",
+                    "otpm": OTPM_LIMIT,
+                },
+                "model_info": {"id": group},
+            }
+            for group in GROUPS
+        ],
+        litellm_settings={"cache": False},
+        router_settings={"optional_pre_call_checks": ["enforce_model_rate_limits"], "num_retries": 0},
+    )
+
+
+@pytest.fixture(scope="module")
+def rig(tmp_path_factory: pytest.TempPathFactory) -> Iterator[Rig]:
+    directory: Final = tmp_path_factory.mktemp("otpm-fraction")
+    gates: Final[SimpleQueue[threading.Event]] = SimpleQueue()
+    with (
+        gateway_from_environment() as gateway,
+        wire_server(_reply_for(gates)) as upstream,
+        owned_proxy_process(
+            gateway,
+            directory,
+            {"NO_MAX_TOKENS_TPM_RESERVATION_FRACTION": str(FRACTION)},
+            config=_config(directory, upstream),
+        ) as owned,
+    ):
+        yield Rig(owned, upstream, gates)
+
+
+def _chat(rig: Rig, group: str, **params: int | bool) -> httpx.Response:
+    return rig.owned.gateway.request(
+        "POST",
+        "/v1/chat/completions",
+        {"model": group, "messages": [{"role": "user", "content": f"fraction {uuid.uuid4().hex}"}], **params},
+    )
+
+
+def _await_forwarded_chat(upstream: Wire) -> Request:
+    request: Final = upstream.received.get(timeout=60)
+    return _await_forwarded_chat(upstream) if is_model_info_probe(request) else request
+
+
+def _utc_minute() -> str:
+    return datetime.now(UTC).strftime("%Y-%m-%d %H:%M")
+
+
+def _admissions_beside_a_held_stream(rig: Rig, group: str) -> Admissions:
+    release: Final = threading.Event()
+    rig.gates.put(release)
+    started: Final = _utc_minute()
+    with ThreadPoolExecutor(max_workers=1) as pool:
+        held: Final = pool.submit(_chat, rig, group, stream=True)
+        try:
+            forwarded: Final = JSON_OBJECT.validate_json(_await_forwarded_chat(rig.upstream).body)
+            over: Final = _chat(rig, group, max_tokens=OTPM_LIMIT - DEFAULT_RESERVATION + 1)
+            fits: Final = _chat(rig, group, max_tokens=OTPM_LIMIT - DEFAULT_RESERVATION)
+            ended: Final = _utc_minute()
+        finally:
+            release.set()
+        return Admissions(
+            held_forwarded_max_tokens="max_tokens" in forwarded,
+            statuses=(over.status_code, fits.status_code, held.result(timeout=60).status_code),
+            one_minute=started == ended,
+        )
+
+
+def test_reservation_fraction_env_var_sets_what_a_request_without_max_tokens_holds(rig: Rig) -> None:
+    first: Final = _admissions_beside_a_held_stream(rig, GROUPS[0])
+    admissions: Final = first if first.one_minute else _admissions_beside_a_held_stream(rig, GROUPS[1])
+
+    assert admissions == Admissions(held_forwarded_max_tokens=False, statuses=(429, 200, 200), one_minute=True)
diff --git a/tests/unit/litellm_core_utils/test_env_utils.py b/tests/unit/litellm_core_utils/test_env_utils.py
index 1ddd172e274..89b091e47c2 100644
--- a/tests/unit/litellm_core_utils/test_env_utils.py
+++ b/tests/unit/litellm_core_utils/test_env_utils.py
@@ -6,6 +6,7 @@ import pytest
 from litellm._logging import verbose_logger
 from litellm.litellm_core_utils.env_utils import (
     get_env_float,
+    get_env_float_in_range,
     get_env_float_or_none,
     get_env_int,
     get_env_int_or_none,
@@ -94,3 +95,12 @@ def test_unparsable_stdout_log_limit_does_not_break_logging(
     assert "first line" in messages
     assert "second line" in messages
     assert len([message for message in messages if raw in message]) == 1
+
+
+@pytest.mark.parametrize(("raw", "expected"), [("0.5", 0.5), ("1", 1.0), ("4", 0.25), ("0", 0.25), ("half", 0.25)])
+def test_float_in_range_keeps_values_inside_the_range_and_falls_back_otherwise(
+    monkeypatch: pytest.MonkeyPatch, raw: str, expected: float
+) -> None:
+    monkeypatch.setenv("ENV_UTILS_TEST_FRACTION", raw)
+
+    assert get_env_float_in_range("ENV_UTILS_TEST_FRACTION", 0.25, 0.01, 1.0) == expected
diff --git a/tests/unit/test_constants.py b/tests/unit/test_constants.py
index 99b049f1803..d9c34e95364 100644
--- a/tests/unit/test_constants.py
+++ b/tests/unit/test_constants.py
@@ -19,7 +19,14 @@ from unittest.mock import patch
 
 
 _ENV_HELPERS = frozenset(
-    {"get_env_int", "get_env_float", "get_env_int_in_range", "get_env_int_or_none", "get_env_float_or_none"}
+    {
+        "get_env_int",
+        "get_env_float",
+        "get_env_int_in_range",
+        "get_env_float_in_range",
+        "get_env_int_or_none",
+        "get_env_float_or_none",
+    }
 )
 
 
diff --git a/tests/unit/test_router/test_io_token_rate_limits.py b/tests/unit/test_router/test_io_token_rate_limits.py
index 05921aa70b3..e5ff4531f84 100644
--- a/tests/unit/test_router/test_io_token_rate_limits.py
+++ b/tests/unit/test_router/test_io_token_rate_limits.py
@@ -3,6 +3,8 @@ Tests for separate ITPM/OTPM deployment rate limits (enforce_model_rate_limits).
 """
 
 import asyncio
+from collections.abc import Awaitable, Callable, Mapping
+from datetime import datetime
 from typing import Final
 
 import pytest
@@ -10,13 +12,16 @@ import pytest
 import litellm
 from litellm import Router
 from litellm.caching.dual_cache import DualCache
+from litellm.constants import NO_MAX_TOKENS_TPM_RESERVATION_FRACTION
+from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObject
+from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER
 from litellm.router_utils.pre_call_checks.io_token_rate_limit_check import (
     ITPM_CACHE_KEY,
     ITPM_RESERVED_KEY,
     OTPM_CACHE_KEY,
     OTPM_RESERVED_KEY,
+    _explicit_max_tokens,
     _reservation_value,
-    _resolve_max_tokens,
     async_io_token_pre_call_check,
     async_io_token_reconcile_success,
     build_io_token_rate_limit_headers,
@@ -30,7 +35,16 @@ from litellm.router_utils.pre_call_checks.io_token_rate_limit_check import (
 from litellm.router_utils.pre_call_checks.model_rate_limit_check import (
     ModelRateLimitingCheck,
 )
+from litellm.types.router import RouterCacheEnum
 from litellm.types.utils import ModelResponse, Usage
+from litellm.utils import get_utc_datetime
+
+MANTLE_OPUS = "bedrock_mantle/anthropic.claude-opus-4-7"
+MANTLE_OPUS_MAX_OUTPUT = litellm.get_model_info(model=MANTLE_OPUS)["max_output_tokens"]
+UNMAPPED_MODEL = "openai/litellm-io-unmapped-model"
+UNMAPPED_MODEL_DEFAULT_MAX_OUTPUT = 4096
+AZURE_BASE_MODEL = "azure/gpt-5"
+AZURE_BASE_MODEL_MAX_OUTPUT = litellm.get_model_info(model=AZURE_BASE_MODEL)["max_output_tokens"]
 
 
 class TestIOTokenRateLimitHelpers:
@@ -48,13 +62,23 @@ class TestIOTokenRateLimitHelpers:
         # A real non-zero estimate is reserved as-is.
         assert _reservation_value(42, 100) == 42
 
-    def test_resolve_max_tokens_respects_explicit_zero(self):
-        deployment = {"litellm_params": {"model": "openai/gpt-4o-mini"}}
-        # An explicit max_tokens=0 is honored, not replaced by the model default.
-        assert _resolve_max_tokens({"max_tokens": 0}, deployment) == 0
-        # max_completion_tokens is the fallback only when max_tokens is absent.
-        assert _resolve_max_tokens({"max_completion_tokens": 12}, deployment) == 12
-        assert _resolve_max_tokens({"max_output_tokens": 9}, deployment) == 9
+    @pytest.mark.parametrize(
+        "request_kwargs, expected",
+        [
+            ({"max_tokens": 0}, 0),
+            ({"max_completion_tokens": 12}, 12),
+            ({"max_output_tokens": 9}, 9),
+            ({"max_tokens": 5, "max_completion_tokens": 12}, 5),
+            ({"max_tokens": None, "max_output_tokens": 9}, 9),
+            ({"max_tokens": [100]}, None),
+            ({"messages": []}, None),
+            (None, None),
+        ],
+    )
+    def test_explicit_max_tokens_reads_every_output_cap_key(
+        self, request_kwargs: dict[str, object] | None, expected: int | None
+    ):
+        assert _explicit_max_tokens(request_kwargs) == expected
 
     def test_build_io_token_rate_limit_headers(self):
         headers = build_io_token_rate_limit_headers(
@@ -386,6 +410,244 @@ class TestModelRateLimitingCheckIOTokens:
         normal_output_otpm_key = normal_output_kwargs["metadata"][OTPM_CACHE_KEY]
         assert await dual_cache.async_get_cache(key=normal_output_otpm_key) == 5
 
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize("use_sync_check", [False, True])
+    @pytest.mark.parametrize(
+        "model, otpm_limit",
+        [
+            (MANTLE_OPUS, MANTLE_OPUS_MAX_OUTPUT // 2),
+            (MANTLE_OPUS, MANTLE_OPUS_MAX_OUTPUT - 1),
+            (UNMAPPED_MODEL, 1000),
+            (UNMAPPED_MODEL, 3),
+        ],
+    )
+    async def test_request_without_max_tokens_is_admitted_below_model_max_output(
+        self, model: str, otpm_limit: int, use_sync_check: bool
+    ):
+        dual_cache: Final = DualCache()
+        check: Final = ModelRateLimitingCheck(dual_cache=dual_cache)
+        deployment: Final = {
+            "litellm_params": {"model": model, "otpm": otpm_limit},
+            "model_info": {"id": f"io-no-max-tokens-{otpm_limit}"},
+            "model_name": "no-max-tokens",
+        }
+        request_kwargs: Final = {"messages": [{"role": "user", "content": "hello"}], "metadata": {}}
+        set_io_token_rate_limit_request_kwargs(request_kwargs)
+
+        if use_sync_check:
+            check.pre_call_check(deployment)
+        else:
+            await check.async_pre_call_check(deployment)
+
+        reserved: Final = request_kwargs["metadata"][OTPM_RESERVED_KEY]
+        assert isinstance(reserved, int)
+        assert 0 < reserved < otpm_limit
+        assert await dual_cache.async_get_cache(key=request_kwargs["metadata"][OTPM_CACHE_KEY]) == reserved
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "model, otpm_limit",
+        [(MANTLE_OPUS, MANTLE_OPUS_MAX_OUTPUT), (UNMAPPED_MODEL, UNMAPPED_MODEL_DEFAULT_MAX_OUTPUT)],
+    )
+    async def test_concurrent_requests_without_max_tokens_share_otpm_without_overshoot(
+        self, model: str, otpm_limit: int
+    ):
+        dual_cache: Final = DualCache()
+        check: Final = ModelRateLimitingCheck(dual_cache=dual_cache)
+        deployment: Final = {
+            "litellm_params": {"model": model, "otpm": otpm_limit},
+            "model_info": {"id": "io-no-max-tokens-race-id"},
+            "model_name": "no-max-tokens",
+        }
+
+        async def _attempt() -> dict[str, object] | None:
+            request_kwargs: Final = {"messages": [{"role": "user", "content": "hi"}], "metadata": {}}
+            set_io_token_rate_limit_request_kwargs(request_kwargs)
+            try:
+                await check.async_pre_call_check(deployment)
+            except litellm.RateLimitError:
+                return None
+            return request_kwargs["metadata"]
+
+        admitted: Final = [m for m in await asyncio.gather(*[_attempt() for _ in range(8)]) if m is not None]
+        otpm_key: Final = admitted[0][OTPM_CACHE_KEY]
+
+        assert len(admitted) == round(1 / NO_MAX_TOKENS_TPM_RESERVATION_FRACTION)
+        assert {m[OTPM_CACHE_KEY] for m in admitted} == {otpm_key}
+        assert await dual_cache.async_get_cache(key=otpm_key) == sum(m[OTPM_RESERVED_KEY] for m in admitted)
+        assert await dual_cache.async_get_cache(key=otpm_key) <= otpm_limit
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "model, model_max_output",
+        [(MANTLE_OPUS, MANTLE_OPUS_MAX_OUTPUT), (UNMAPPED_MODEL, UNMAPPED_MODEL_DEFAULT_MAX_OUTPUT)],
+    )
+    async def test_request_without_max_tokens_reserves_model_max_output_when_otpm_allows(
+        self, model: str, model_max_output: int
+    ):
+        dual_cache: Final = DualCache()
+        check: Final = ModelRateLimitingCheck(dual_cache=dual_cache)
+        deployment: Final = {
+            "litellm_params": {"model": model, "otpm": model_max_output * 10},
+            "model_info": {"id": "io-no-max-tokens-roomy-id"},
+            "model_name": "roomy",
+        }
+        request_kwargs: Final = {"messages": [{"role": "user", "content": "hello"}], "metadata": {}}
+        set_io_token_rate_limit_request_kwargs(request_kwargs)
+
+        await check.async_pre_call_check(deployment)
+
+        assert request_kwargs["metadata"][OTPM_RESERVED_KEY] == model_max_output
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize("use_sync_check", [False, True])
+    async def test_base_model_does_not_change_the_default_otpm_reservation(self, use_sync_check: bool):
+        check: Final = ModelRateLimitingCheck(dual_cache=DualCache())
+        otpm_limit: Final = AZURE_BASE_MODEL_MAX_OUTPUT * 10
+
+        async def _reserved(model_info: dict[str, str]) -> int:
+            request_kwargs: Final = {"messages": [{"role": "user", "content": "hello"}], "metadata": {}}
+            set_io_token_rate_limit_request_kwargs(request_kwargs)
+            deployment: Final = {
+                "litellm_params": {"model": "azure/litellm-io-custom-deployment", "otpm": otpm_limit},
+                "model_info": model_info,
+                "model_name": "custom-name",
+            }
+            if use_sync_check:
+                check.pre_call_check(deployment)
+            else:
+                await check.async_pre_call_check(deployment)
+            return request_kwargs["metadata"][OTPM_RESERVED_KEY]
+
+        with_base_model: Final = await _reserved({"id": "io-with-base-model", "base_model": AZURE_BASE_MODEL})
+        without_base_model: Final = await _reserved({"id": "io-without-base-model"})
+
+        assert with_base_model == without_base_model
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize("use_sync_check", [False, True])
+    async def test_unparseable_max_tokens_leaves_itpm_uncharged(self, use_sync_check: bool):
+        dual_cache: Final = DualCache()
+        check: Final = ModelRateLimitingCheck(dual_cache=dual_cache)
+        deployment: Final = {
+            "litellm_params": {"model": MANTLE_OPUS, "itpm": 2000, "otpm": 2000},
+            "model_info": {"id": "io-bad-max-tokens-id"},
+            "model_name": "opus",
+        }
+
+        async def _pre_call(request_kwargs: dict[str, object]) -> None:
+            set_io_token_rate_limit_request_kwargs(request_kwargs)
+            if use_sync_check:
+                check.pre_call_check(deployment)
+            else:
+                await check.async_pre_call_check(deployment)
+
+        await _pre_call({"messages": [{"role": "user", "content": "hello there"}], "max_tokens": "abc", "metadata": {}})
+        valid_kwargs: Final = {
+            "messages": [{"role": "user", "content": "hello there"}],
+            "max_tokens": 1,
+            "metadata": {},
+        }
+        await _pre_call(valid_kwargs)
+
+        itpm_counter: Final = await dual_cache.async_get_cache(key=valid_kwargs["metadata"][ITPM_CACHE_KEY])
+        assert itpm_counter == valid_kwargs["metadata"][ITPM_RESERVED_KEY]
+
+    @pytest.mark.asyncio
+    async def test_explicit_max_tokens_above_default_share_is_reserved_in_full(self):
+        dual_cache: Final = DualCache()
+        check: Final = ModelRateLimitingCheck(dual_cache=dual_cache)
+        deployment: Final = {
+            "litellm_params": {"model": MANTLE_OPUS, "otpm": 100},
+            "model_info": {"id": "io-explicit-max-tokens-id"},
+            "model_name": "opus",
+        }
+        request_kwargs: Final = {"messages": [{"role": "user", "content": "hello"}], "max_tokens": 100, "metadata": {}}
+        set_io_token_rate_limit_request_kwargs(request_kwargs)
+
+        await check.async_pre_call_check(deployment)
+
+        assert request_kwargs["metadata"][OTPM_RESERVED_KEY] == 100
+        set_io_token_rate_limit_request_kwargs({"messages": [{"role": "user", "content": "hi"}], "metadata": {}})
+        with pytest.raises(litellm.RateLimitError):
+            await check.async_pre_call_check(deployment)
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize("use_sync_check", [False, True])
+    async def test_deployment_max_tokens_sets_the_reservation_unless_the_request_sets_one(self, use_sync_check: bool):
+        check: Final = ModelRateLimitingCheck(dual_cache=DualCache())
+        deployment: Final = {
+            "litellm_params": {"model": MANTLE_OPUS, "otpm": 4000, "max_tokens": 100},
+            "model_info": {"id": "io-deployment-max-tokens-id"},
+            "model_name": "opus",
+        }
+        without_cap: Final = {"messages": [{"role": "user", "content": "hello"}], "metadata": {}}
+        with_cap: Final = {"messages": [{"role": "user", "content": "hello"}], "max_tokens": 300, "metadata": {}}
+
+        for request_kwargs in (without_cap, with_cap):
+            set_io_token_rate_limit_request_kwargs(request_kwargs)
+            if use_sync_check:
+                check.pre_call_check(deployment)
+            else:
+                await check.async_pre_call_check(deployment)
+
+        assert without_cap["metadata"][OTPM_RESERVED_KEY] == 100
+        assert with_cap["metadata"][OTPM_RESERVED_KEY] == 300
+
+    @pytest.mark.asyncio
+    async def test_deployment_cap_sets_the_reservation_only_through_the_param_its_api_sends(self):
+        check: Final = ModelRateLimitingCheck(dual_cache=DualCache())
+        chat: Final = {"messages": [{"role": "user", "content": "hello"}]}
+        responses: Final = {"input": "hello"}
+
+        async def reserved(deployment_cap: Mapping[str, int], request_shape: Mapping[str, object]) -> int:
+            request_kwargs: Final = {**request_shape, "metadata": {}}
+            set_io_token_rate_limit_request_kwargs(request_kwargs)
+            await check.async_pre_call_check(
+                {
+                    "litellm_params": {"model": MANTLE_OPUS, "otpm": 4000, **deployment_cap},
+                    "model_info": {"id": f"io-sent-cap-{sorted(deployment_cap)}-{sorted(request_shape)}"},
+                    "model_name": "opus",
+                }
+            )
+            return request_kwargs["metadata"][OTPM_RESERVED_KEY]
+
+        chat_default: Final = await reserved({}, chat)
+        responses_default: Final = await reserved({}, responses)
+
+        assert chat_default == responses_default > 100
+        assert await reserved({"max_tokens": 100}, chat) == 100
+        assert await reserved({"max_completion_tokens": 100}, chat) == 100
+        assert await reserved({"max_output_tokens": 100}, chat) == chat_default
+        assert await reserved({"max_output_tokens": 100}, responses) == 100
+        assert await reserved({"max_tokens": 100}, responses) == responses_default
+        assert await reserved({"max_completion_tokens": 100}, responses) == responses_default
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize("use_sync_check", [False, True])
+    async def test_deployment_cap_above_the_default_reserves_the_default(self, use_sync_check: bool):
+        check: Final = ModelRateLimitingCheck(dual_cache=DualCache())
+        otpm_limit: Final = UNMAPPED_MODEL_DEFAULT_MAX_OUTPUT * 5
+
+        async def reserved(deployment_cap: Mapping[str, int]) -> int:
+            request_kwargs: Final = {"messages": [{"role": "user", "content": "hello"}], "metadata": {}}
+            set_io_token_rate_limit_request_kwargs(request_kwargs)
+            deployment: Final = {
+                "litellm_params": {"model": UNMAPPED_MODEL, "otpm": otpm_limit, **deployment_cap},
+                "model_info": {"id": f"io-deployment-cap-above-default-{deployment_cap}"},
+                "model_name": "unmapped",
+            }
+            if use_sync_check:
+                check.pre_call_check(deployment)
+            else:
+                await check.async_pre_call_check(deployment)
+            return request_kwargs["metadata"][OTPM_RESERVED_KEY]
+
+        default: Final = await reserved({})
+
+        assert await reserved({"max_tokens": default + 1}) == default
+        assert await reserved({"max_tokens": otpm_limit * 2}) == default
+
     def test_sync_io_pre_call_reserves_and_reconciles(self):
         from litellm.utils import get_utc_datetime
 
@@ -415,9 +677,9 @@ class TestModelRateLimitingCheckIOTokens:
             "standard_logging_object": {
                 "model_id": "io-sync-id",
                 "hidden_params": {"litellm_model_name": "bedrock_mantle/anthropic.claude-opus-4-7"},
-                "metadata": dict(request_kwargs["metadata"]),
+                "metadata": {},
             },
-            "metadata": request_kwargs["metadata"],
+            "litellm_params": {"metadata": request_kwargs["metadata"]},
         }
         response = ModelResponse(
             choices=[{"message": {"role": "assistant", "content": "hi"}, "index": 0, "finish_reason": "stop"}],
@@ -709,6 +971,32 @@ class TestModelRateLimitingCheckIOTokens:
 
         assert await dual_cache.async_get_cache(key=itpm_key) == 4
 
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize("use_sync_reconcile", [False, True])
+    async def test_reconcile_charges_usage_above_the_reservation_to_the_minute_it_finished_in(
+        self, use_sync_reconcile: bool
+    ):
+        dual_cache: Final = DualCache()
+        counter: Final = "global_router:io-late-id:bedrock_mantle/test:otpm"
+        reserved_minute_key: Final = f"{counter}:99-99"
+        await dual_cache.async_increment_cache(key=reserved_minute_key, value=10, ttl=60)
+        kwargs: Final = {"metadata": {ITPM_RESERVED_KEY: 0, OTPM_RESERVED_KEY: 10, OTPM_CACHE_KEY: reserved_minute_key}}
+        response: Final = ModelResponse(
+            choices=[{"message": {"role": "assistant", "content": "hi"}, "index": 0, "finish_reason": "stop"}],
+            usage=Usage(prompt_tokens=4, completion_tokens=25, total_tokens=29),
+        )
+        minute_before: Final = get_utc_datetime().strftime("%H-%M")
+
+        if use_sync_reconcile:
+            io_token_reconcile_success(dual_cache, kwargs, response)
+        else:
+            await async_io_token_reconcile_success(dual_cache, kwargs, response)
+
+        finished_minutes: Final = {minute_before, get_utc_datetime().strftime("%H-%M")}
+        charged: Final = [await dual_cache.async_get_cache(key=f"{counter}:{minute}") for minute in finished_minutes]
+        assert await dual_cache.async_get_cache(key=reserved_minute_key) == 10
+        assert sum(value or 0 for value in charged) == 25 - 10
+
     @pytest.mark.asyncio
     async def test_reconcile_missing_usage_keeps_reservation(self):
         dual_cache = DualCache()
@@ -799,16 +1087,16 @@ class TestModelRateLimitingCheckIOTokens:
 
         assert await dual_cache.async_get_cache(key=itpm_key) == 4
 
-    def test_sync_reconcile_anthropic_dict_usage(self):
+    def test_sync_reconcile_anthropic_dict_usage_counts_uncached_input_once(self):
         dual_cache = DualCache()
         itpm_key = "global_router:io-anthropic:bedrock_mantle/test:itpm:00-00"
         otpm_key = "global_router:io-anthropic:bedrock_mantle/test:otpm:00-00"
-        dual_cache.set_cache(key=itpm_key, value=6, ttl=60)
+        dual_cache.set_cache(key=itpm_key, value=10, ttl=60)
         dual_cache.set_cache(key=otpm_key, value=4, ttl=60)
 
         kwargs = {
             "metadata": {
-                ITPM_RESERVED_KEY: 6,
+                ITPM_RESERVED_KEY: 10,
                 OTPM_RESERVED_KEY: 4,
                 ITPM_CACHE_KEY: itpm_key,
                 OTPM_CACHE_KEY: otpm_key,
@@ -816,12 +1104,17 @@ class TestModelRateLimitingCheckIOTokens:
         }
         response = {
             "type": "message",
-            "usage": {"input_tokens": 3, "output_tokens": 2, "cache_read_input_tokens": 1},
+            "usage": {
+                "input_tokens": 3,
+                "output_tokens": 2,
+                "cache_read_input_tokens": 1,
+                "cache_creation_input_tokens": 4,
+            },
         }
 
         io_token_reconcile_success(dual_cache, kwargs, response)
 
-        assert dual_cache.get_cache(key=itpm_key) == 2
+        assert dual_cache.get_cache(key=itpm_key) == 3 + 4
         assert dual_cache.get_cache(key=otpm_key) == 2
 
     @pytest.mark.asyncio
@@ -958,7 +1251,214 @@ class TestModelRateLimitingCheckIOTokens:
         assert current == 0
 
 
+ROUTER_IO_MODEL: Final = "anthropic/claude-haiku-5-5"
+RouterCall = Callable[[Router, str | Exception], Awaitable[tuple[int, int]]]
+
+
+def _router_with_io_limits() -> Router:
+    return Router(
+        model_list=[
+            {
+                "model_name": "limited",
+                "litellm_params": {"model": ROUTER_IO_MODEL, "api_key": "sk-test", "itpm": 50000, "otpm": 50000},
+            }
+        ],
+        optional_pre_call_checks=["enforce_model_rate_limits"],
+        num_retries=1,
+    )
+
+
+def _current_minute() -> str:
+    return get_utc_datetime().strftime("%H-%M")
+
+
+def _counter(router: Router, template: RouterCacheEnum, minutes: frozenset[str]) -> int:
+    deployment: Final = router.model_list[0]
+    return sum(
+        router.cache.get_cache(
+            key=template.value.format(
+                id=deployment["model_info"]["id"],
+                model=deployment["litellm_params"]["model"],
+                current_minute=minute,
+            )
+        )
+        or 0
+        for minute in minutes
+    )
+
+
+async def _io_counters_since(router: Router, first_minute: str) -> tuple[int, int]:
+    await asyncio.sleep(0)
+    await asyncio.wait_for(GLOBAL_LOGGING_WORKER.flush(), timeout=10)
+    minutes: Final = frozenset({first_minute, _current_minute()})
+    return _counter(router, RouterCacheEnum.ITPM, minutes), _counter(router, RouterCacheEnum.OTPM, minutes)
+
+
+async def _sdk_chat(router: Router, mock_response: str | Exception) -> tuple[int, int]:
+    response: Final = await router.acompletion(
+        model="limited",
+        messages=[{"role": "user", "content": "hello there"}],
+        max_tokens=100,
+        mock_response=mock_response,
+    )
+    return response.usage.prompt_tokens, response.usage.completion_tokens
+
+
+async def _proxy_chat(router: Router, mock_response: str | Exception) -> tuple[int, int]:
+    response: Final = await router.acompletion(
+        model="limited",
+        messages=[{"role": "user", "content": "hello there"}],
+        max_tokens=100,
+        metadata={"user_api_key_hash": "hashed-key"},
+        mock_response=mock_response,
+    )
+    return response.usage.prompt_tokens, response.usage.completion_tokens
+
+
+async def _proxy_responses(router: Router, mock_response: str | Exception) -> tuple[int, int]:
+    response: Final = await router.aresponses(
+        model="limited",
+        input="hello there",
+        max_output_tokens=100,
+        litellm_metadata={"user_api_key_hash": "hashed-key"},
+        mock_response=mock_response,
+    )
+    return response.usage.input_tokens, response.usage.output_tokens
+
+
+async def _proxy_messages(router: Router, mock_response: str | Exception) -> tuple[int, int]:
+    response: Final = await router.aanthropic_messages(
+        model="limited",
+        messages=[{"role": "user", "content": "hello there"}],
+        max_tokens=100,
+        litellm_metadata={"user_api_key_hash": "hashed-key"},
+        mock_response=mock_response,
+    )
+    return response["usage"]["input_tokens"], response["usage"]["output_tokens"]
+
+
+ProxyCallSharingLogging = Callable[[Router, str | Exception, LiteLLMLoggingObject], Awaitable[object]]
+PROXY_MESSAGES: Final = [{"role": "user", "content": "hello there"}]
+
+
+def _logging_obj_shared_across_attempts(original_function: str) -> LiteLLMLoggingObject:
+    logging_obj, _ = litellm.utils.function_setup(
+        original_function,
+        litellm.utils.Rules(),
+        datetime.now(),
+        model="limited",
+        messages=PROXY_MESSAGES,
+        litellm_call_id="proxy-call",
+    )
+    return logging_obj
+
+
+async def _proxy_chat_sharing_logging(
+    router: Router, mock_error: str | Exception, logging_obj: LiteLLMLoggingObject
+) -> object:
+    return await router.acompletion(
+        model="limited",
+        messages=PROXY_MESSAGES,
+        max_tokens=100,
+        metadata={"user_api_key_hash": "hashed-key"},
+        mock_response=mock_error,
+        litellm_call_id="proxy-call",
+        litellm_logging_obj=logging_obj,
+    )
+
+
+async def _proxy_responses_sharing_logging(
+    router: Router, mock_error: str | Exception, logging_obj: LiteLLMLoggingObject
+) -> object:
+    return await router.aresponses(
+        model="limited",
+        input="hello there",
+        max_output_tokens=100,
+        litellm_metadata={"user_api_key_hash": "hashed-key"},
+        mock_response=mock_error,
+        litellm_call_id="proxy-call",
+        litellm_logging_obj=logging_obj,
+    )
+
+
+async def _proxy_messages_sharing_logging(
+    router: Router, mock_error: str | Exception, logging_obj: LiteLLMLoggingObject
+) -> object:
+    return await router.aanthropic_messages(
+        model="limited",
+        messages=PROXY_MESSAGES,
+        max_tokens=100,
+        litellm_metadata={"user_api_key_hash": "hashed-key"},
+        mock_response=mock_error,
+        litellm_call_id="proxy-call",
+        litellm_logging_obj=logging_obj,
+    )
+
+
 class TestRouterIOTokenIntegration:
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "call",
+        [_sdk_chat, _proxy_chat, _proxy_responses, _proxy_messages],
+        ids=["sdk_chat", "proxy_chat_metadata", "proxy_responses_litellm_metadata", "proxy_messages_litellm_metadata"],
+    )
+    async def test_success_reconciles_io_counters_to_real_usage(self, call: RouterCall):
+        router: Final = _router_with_io_limits()
+        first_minute: Final = _current_minute()
+
+        usage: Final = await call(router, "hi")
+
+        assert await _io_counters_since(router, first_minute) == usage
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        ("call", "mock_error"),
+        [
+            (
+                _proxy_responses,
+                litellm.InternalServerError(message="mock 500", llm_provider="anthropic", model=ROUTER_IO_MODEL),
+            ),
+            (_proxy_messages, "litellm.InternalServerError"),
+        ],
+        ids=["proxy_responses_litellm_metadata", "proxy_messages_litellm_metadata"],
+    )
+    async def test_retried_failure_refunds_each_io_reservation_once(
+        self, call: RouterCall, mock_error: str | Exception
+    ):
+        router: Final = _router_with_io_limits()
+        first_minute: Final = _current_minute()
+
+        with pytest.raises(litellm.InternalServerError):
+            await call(router, mock_error)
+
+        assert await _io_counters_since(router, first_minute) == (0, 0)
+
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        ("call", "original_function", "mock_error"),
+        [
+            (_proxy_chat_sharing_logging, "acompletion", "litellm.InternalServerError"),
+            (
+                _proxy_responses_sharing_logging,
+                "aresponses",
+                litellm.InternalServerError(message="mock 500", llm_provider="anthropic", model=ROUTER_IO_MODEL),
+            ),
+            (_proxy_messages_sharing_logging, "anthropic_messages", "litellm.InternalServerError"),
+        ],
+        ids=["proxy_chat", "proxy_responses", "proxy_messages"],
+    )
+    async def test_retried_failure_sharing_one_logging_object_refunds_every_attempt(
+        self, call: ProxyCallSharingLogging, original_function: str, mock_error: str | Exception
+    ):
+        router: Final = _router_with_io_limits()
+        first_minute: Final = _current_minute()
+
+        with pytest.raises(litellm.InternalServerError):
+            await call(router, mock_error, _logging_obj_shared_across_attempts(original_function))
+
+        assert await _io_counters_since(router, first_minute) == (0, 0)
+
     @pytest.mark.asyncio
     async def test_model_group_info_aggregates_io_limits(self):
         router = Router(