diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index 350e5403e4c..eb223c2f988 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -111,6 +111,7 @@ from litellm.types.mcp import MCPPostCallResponseObject
 from litellm.types.prompts.init_prompts import PromptSpec
 from litellm.types.rerank import RerankResponse
 from litellm.types.utils import (
+    DEPLOYMENT_SCOPED_PRICING_FIELDS,
     CachingDetails,
     CallTypes,
     CostBreakdown,
@@ -255,6 +256,7 @@ _STANDARD_LOGGING_METADATA_KEYS: Final[frozenset[str]] = frozenset(StandardLoggi
 
 # Cache custom pricing keys as frozenset for O(1) lookups instead of looping through 49 keys
 _CUSTOM_PRICING_KEYS: Final[frozenset[str]] = frozenset(CustomPricingLiteLLMParams.model_fields.keys())
+_MODEL_INFO_CUSTOM_PRICING_KEYS: Final[frozenset[str]] = _CUSTOM_PRICING_KEYS | DEPLOYMENT_SCOPED_PRICING_FIELDS
 
 sentry_sdk_instance = None
 capture_exception = None
@@ -5033,7 +5035,9 @@ def use_custom_pricing_for_model(litellm_params: dict | None) -> bool:
     """
     Check if the model uses custom pricing
 
-    Returns True if any of `SPECIAL_MODEL_INFO_PARAMS` are present in `litellm_params` or `model_info`
+    Returns True if any custom pricing field is present in `litellm_params`, or if
+    any custom pricing or deployment-scoped pricing field (such as
+    ``off_peak_pricing``) is present in the metadata ``model_info``
     """
     if litellm_params is None:
         return False
@@ -5051,7 +5055,7 @@ def use_custom_pricing_for_model(litellm_params: dict | None) -> bool:
         model_info: dict = metadata.get("model_info", {}) or {}
 
         if model_info:
-            matching_keys = _CUSTOM_PRICING_KEYS & model_info.keys()
+            matching_keys = _MODEL_INFO_CUSTOM_PRICING_KEYS & model_info.keys()
             for key in matching_keys:
                 if model_info.get(key) is not None:
                     return True
diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py
index 19e3f624268..b34c416cd40 100644
--- a/litellm/litellm_core_utils/llm_cost_calc/utils.py
+++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py
@@ -2,10 +2,12 @@
 ## Helper utilities for cost_per_token()
 
 import re
-from collections.abc import Mapping
+from collections.abc import Mapping, Sequence
 from dataclasses import dataclass
+from datetime import datetime, timezone, tzinfo
 from types import MappingProxyType
 from typing import Any, Final, Literal, TypedDict, cast
+from zoneinfo import ZoneInfo, ZoneInfoNotFoundError
 
 import litellm
 from litellm._logging import verbose_logger
@@ -290,10 +292,187 @@ def _get_tiered_base_costs(model_info: ModelInfo, usage: Usage) -> tuple[float,
     )
 
 
+def _is_within_off_peak_window(off_peak_hours_utc: str | Sequence[str], current_time: datetime | None = None) -> bool:
+    """Return True if current_time (UTC, defaulting to now) falls inside any off-peak window.
+
+    off_peak_hours_utc is a "HH:MM-HH:MM" string in UTC, or a list of such strings for providers
+    with multiple daily windows (e.g. ["16:30-00:30", "04:00-06:00"]). A window may wrap past
+    midnight, and a window whose start equals its end covers the whole day. The start is
+    inclusive and the end is exclusive; malformed windows are ignored.
+
+    An aware current_time is converted to UTC. A naive one is taken to already be UTC rather
+    than being localised, so callers must pass datetime.now(timezone.utc), never datetime.now(),
+    or every window shifts by the host's offset.
+    """
+    reference: Final = current_time if current_time is not None else datetime.now(timezone.utc)
+    now: Final = (reference.astimezone(timezone.utc) if reference.tzinfo is not None else reference).time()
+    windows: Final = (off_peak_hours_utc,) if isinstance(off_peak_hours_utc, str) else off_peak_hours_utc
+    for window in windows:
+        try:
+            start_str, end_str = window.split("-")
+            start = datetime.strptime(start_str.strip(), "%H:%M").replace(tzinfo=timezone.utc).time()
+            end = datetime.strptime(end_str.strip(), "%H:%M").replace(tzinfo=timezone.utc).time()
+        except (ValueError, AttributeError):
+            continue
+        if start < end:
+            if start <= now < end:
+                return True
+        elif now >= start or now < end:
+            return True
+    return False
+
+
+_WEEKDAY_NUMBERS: Final = MappingProxyType(
+    {
+        "mon": 1,
+        "monday": 1,
+        "tue": 2,
+        "tues": 2,
+        "tuesday": 2,
+        "wed": 3,
+        "wednesday": 3,
+        "thu": 4,
+        "thur": 4,
+        "thurs": 4,
+        "thursday": 4,
+        "fri": 5,
+        "friday": 5,
+        "sat": 6,
+        "saturday": 6,
+        "sun": 7,
+        "sunday": 7,
+    }
+)
+
+
+def _normalize_weekday(value: object) -> int | None:
+    if isinstance(value, bool):
+        return None
+    if isinstance(value, int):
+        return value if 1 <= value <= 7 else None
+    if isinstance(value, str):
+        return _WEEKDAY_NUMBERS.get(value.strip().lower())
+    return None
+
+
+def _weekday_calendar(weekday_timezone: object) -> tzinfo:
+    if isinstance(weekday_timezone, str) and weekday_timezone.strip():
+        try:
+            return ZoneInfo(weekday_timezone.strip())
+        except (ValueError, ZoneInfoNotFoundError):
+            return timezone.utc
+    return timezone.utc
+
+
+def _matches_weekdays(reference_utc: datetime, weekdays: object, weekday_timezone: object) -> bool:
+    """Return True when reference_utc falls on one of the rule's weekdays, read on the calendar
+    named by weekday_timezone (default UTC). An absent weekdays means every day. The calendar
+    matters even when UTC and vendor-local weekdays agree at every currently priced hour: a
+    window past 16:00 UTC is where an Asia/Shanghai weekday diverges from the UTC one.
+    """
+    if weekdays is None:
+        return True
+    if isinstance(weekdays, str) or not isinstance(weekdays, Sequence):
+        return False
+    allowed: Final = frozenset(day for day in map(_normalize_weekday, weekdays) if day is not None)
+    return reference_utc.astimezone(_weekday_calendar(weekday_timezone)).isoweekday() in allowed
+
+
+def _as_window_strings(value: object) -> tuple[str, ...]:
+    if isinstance(value, str):
+        return (value,)
+    if isinstance(value, Sequence):
+        return tuple(entry for entry in value if isinstance(entry, str))
+    return ()
+
+
+def _is_off_peak(off_peak: Mapping[str, object], current_time: datetime | None = None) -> bool:
+    """Return True when current_time (UTC, defaulting to now) is off-peak under the block's
+    rules: the flat hours_utc windows, which apply every day, or any entry in windows, whose
+    hours apply only on its weekdays.
+    """
+    reference: Final = current_time if current_time is not None else datetime.now(timezone.utc)
+    reference_utc: Final = (
+        reference.astimezone(timezone.utc) if reference.tzinfo is not None else reference.replace(tzinfo=timezone.utc)
+    )
+    flat_windows: Final = _as_window_strings(off_peak.get("hours_utc"))
+    if flat_windows and _is_within_off_peak_window(flat_windows, reference_utc):
+        return True
+    windows: Final = off_peak.get("windows")
+    if isinstance(windows, str) or not isinstance(windows, Sequence):
+        return False
+    weekday_timezone: Final = off_peak.get("weekday_timezone")
+    for rule in windows:
+        if not isinstance(rule, Mapping):
+            continue
+        rule_windows = _as_window_strings(rule.get("hours_utc"))
+        if not rule_windows:
+            continue
+        if not _matches_weekdays(reference_utc, rule.get("weekdays"), weekday_timezone):
+            continue
+        if _is_within_off_peak_window(rule_windows, reference_utc):
+            return True
+    return False
+
+
+def _coerce_off_peak_rate(value: object, default: float) -> float:
+    if isinstance(value, bool):
+        return default
+    if isinstance(value, (int, float)):
+        return float(value)
+    if isinstance(value, str):
+        try:
+            return float(value)
+        except ValueError:
+            return default
+    return default
+
+
+def _apply_off_peak_pricing(
+    model_info: ModelInfo,
+    current_time: datetime | None,
+    prompt_base_cost: float,
+    completion_base_cost: float,
+    cache_read_cost: float,
+) -> tuple[float, float, float]:
+    """Swap in off-peak per-token rates when the current UTC time is inside one of the model's
+    off_peak_pricing rules, the every-day hours_utc windows or a day-of-week-qualified entry in
+    windows. An off-peak rate replaces the rate that would otherwise apply rather than
+    discounting it, so a model that also has tiered or above-threshold pricing bills the flat
+    off-peak rate for the whole request while the window is open. Any rate left unset in
+    off_peak_pricing falls back to the standard rate.
+    """
+    off_peak: Final = model_info.get("off_peak_pricing")
+    if not isinstance(off_peak, Mapping) or not _is_off_peak(off_peak, current_time):
+        return prompt_base_cost, completion_base_cost, cache_read_cost
+    return (
+        _coerce_off_peak_rate(off_peak.get("input_cost_per_token"), prompt_base_cost),
+        _coerce_off_peak_rate(off_peak.get("output_cost_per_token"), completion_base_cost),
+        _coerce_off_peak_rate(off_peak.get("cache_read_input_token_cost"), cache_read_cost),
+    )
+
+
+def _apply_off_peak_to_base_costs(
+    model_info: ModelInfo,
+    current_time: datetime | None,
+    base_costs: tuple[float, float, float, float, float],
+) -> tuple[float, float, float, float, float]:
+    """Apply off-peak rates to an already-resolved set of base costs, whichever pricing path
+    produced them. Cache-creation rates are passed through untouched, since off_peak_pricing
+    has no field for them.
+    """
+    prompt, completion, cache_creation, cache_creation_above_1hr, cache_read = base_costs
+    off_peak_prompt, off_peak_completion, off_peak_cache_read = _apply_off_peak_pricing(
+        model_info, current_time, prompt, completion, cache_read
+    )
+    return (off_peak_prompt, off_peak_completion, cache_creation, cache_creation_above_1hr, off_peak_cache_read)
+
+
 def _get_token_base_cost(
     model_info: ModelInfo,
     usage: Usage,
     service_tier: str | None = None,
+    current_time: datetime | None = None,
     *,
     threshold_is_inclusive: bool = False,
 ) -> tuple[float, float, float, float, float]:
@@ -311,7 +490,7 @@ def _get_token_base_cost(
     """
     tiered_base_costs: Final = _get_tiered_base_costs(model_info=model_info, usage=usage)
     if tiered_base_costs is not None:
-        return tiered_base_costs
+        return _apply_off_peak_to_base_costs(model_info, current_time, tiered_base_costs)
 
     # Get service tier aware cost keys
     input_cost_key: Final = _get_service_tier_cost_key("input_cost_per_token", service_tier)
@@ -345,12 +524,16 @@ def _get_token_base_cost(
         k for k in model_info if k.startswith("input_cost_per_token_above_") and not k.endswith(_SERVICE_TIER_SUFFIXES)
     ]
     if not threshold_keys:
-        return (
-            prompt_base_cost,
-            completion_base_cost,
-            cache_creation_cost,
-            cache_creation_cost_above_1hr,
-            cache_read_cost,
+        return _apply_off_peak_to_base_costs(
+            model_info,
+            current_time,
+            (
+                prompt_base_cost,
+                completion_base_cost,
+                cache_creation_cost,
+                cache_creation_cost_above_1hr,
+                cache_read_cost,
+            ),
         )
 
     # Only sort the threshold keys (typically 1-2 keys instead of 66+)
@@ -451,12 +634,16 @@ def _get_token_base_cost(
             except Exception:
                 continue
 
-    return (
-        prompt_base_cost,
-        completion_base_cost,
-        cache_creation_cost,
-        cache_creation_cost_above_1hr,
-        cache_read_cost,
+    return _apply_off_peak_to_base_costs(
+        model_info,
+        current_time,
+        (
+            prompt_base_cost,
+            completion_base_cost,
+            cache_creation_cost,
+            cache_creation_cost_above_1hr,
+            cache_read_cost,
+        ),
     )
 
 
diff --git a/litellm/router.py b/litellm/router.py
index edff8294c3e..471a1116f44 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -8165,6 +8165,52 @@ class Router:
                 if backend_value is not None:
                     model_info[field] = backend_value
 
+    @staticmethod
+    def _inherit_builtin_base_rates_for_off_peak(
+        model_info: dict,  # mutable-ok: cost-map entry filled in place
+        backend_model: str,
+        custom_llm_provider: str | None,
+    ) -> None:
+        """Fill missing pricing fields on a deployment entry that only sets
+        ``off_peak_pricing``, from the backend model's built-in cost map entry.
+
+        Cost lookup selects the deployment-scoped entry over the shared backend
+        entry only when the deployment entry carries a base pricing field, and
+        ``off_peak_pricing`` is deliberately kept off the shared entry, so a
+        deployment spelling out only its off-peak schedule would otherwise
+        never receive the discount. The backend model's entire canonical cost
+        map entry is copied, field by field, so threshold, tiered,
+        service-tier, cache, character, and per-second rates as well as
+        companion billing fields like ``web_search_billing_unit`` and the
+        regional uplift multipliers all carry over, and peak-hour billing
+        through the deployment entry matches the shared backend entry exactly.
+        The raw ``litellm.model_cost`` entry is the copy source rather than
+        ``get_model_info``'s view of it, since that view synthesizes zero flat
+        token rates for backends without one and storing those would mark a
+        tiered-only backend explicitly priced free. Values are deep-copied to
+        keep the builtin entry isolated. User-specified fields always win;
+        no-op when any base pricing field is already set or the backend model
+        has no canonical entry.
+        """
+        if not model_info.get("off_peak_pricing"):
+            return
+        if any(
+            model_info.get(field) is not None
+            for field in ("input_cost_per_token", "input_cost_per_second", "tiered_pricing")
+        ):
+            return
+        try:
+            backend_info: Final = litellm.get_model_info(model=backend_model, custom_llm_provider=custom_llm_provider)
+        except Exception:  # noqa: BLE001  # get_model_info raises plain Exception for an unmapped backend model
+            return
+        backend_entry: Final = litellm.model_cost.get(backend_info.get("key") or "")
+        if not isinstance(backend_entry, dict):
+            return
+        for field, backend_value in backend_entry.items():
+            if model_info.get(field) is not None or backend_value is None:
+                continue
+            model_info[field] = copy.deepcopy(backend_value)
+
     @staticmethod
     def _inherit_builtin_tiered_output_rate(
         model_info: dict, backend_model: str, custom_llm_provider: str | None
@@ -8253,6 +8299,11 @@ class Router:
                 if deployment.litellm_params.get(field) is not None:
                     _model_info[field] = deployment.litellm_params[field]
 
+            Router._inherit_builtin_base_rates_for_off_peak(
+                model_info=_model_info,
+                backend_model=deployment.litellm_params.model,
+                custom_llm_provider=deployment.litellm_params.custom_llm_provider,
+            )
             if _model_info.get("input_cost_per_token") is not None:
                 Router._inherit_builtin_cache_pricing(
                     model_info=_model_info,
@@ -8994,6 +9045,11 @@ class Router:
             if field_value is not None:
                 _model_info_dict[field] = field_value
 
+        Router._inherit_builtin_base_rates_for_off_peak(
+            model_info=_model_info_dict,
+            backend_model=deployment.litellm_params.model,
+            custom_llm_provider=deployment.litellm_params.custom_llm_provider,
+        )
         if _model_info_dict.get("input_cost_per_token") is not None:
             Router._inherit_builtin_cache_pricing(
                 model_info=_model_info_dict,
@@ -9249,6 +9305,11 @@ class Router:
             field_value = deployment.litellm_params.get(field)
             if field_value is not None:
                 model_info[field] = field_value
+        Router._inherit_builtin_base_rates_for_off_peak(
+            model_info=model_info,
+            backend_model=deployment.litellm_params.model,
+            custom_llm_provider=deployment.litellm_params.custom_llm_provider,
+        )
         if model_info.get("input_cost_per_token") is not None:
             Router._inherit_builtin_cache_pricing(
                 model_info=model_info,
diff --git a/litellm/types/utils.py b/litellm/types/utils.py
index addb7b730de..3a0883b6607 100644
--- a/litellm/types/utils.py
+++ b/litellm/types/utils.py
@@ -193,6 +193,38 @@ class AgenticLoopParams(TypedDict, total=False):
     """The LLM provider name (e.g., 'bedrock', 'anthropic')"""
 
 
+class OffPeakWindow(TypedDict, total=False):
+    """One off-peak rule: UTC time-of-day windows, optionally restricted to weekdays.
+
+    hours_utc is a "HH:MM-HH:MM" string in UTC, or a list of them; a window may wrap past
+    midnight and an equal-ended window covers the whole day. weekdays is a list of days the
+    rule applies on, as ISO-8601 numbers (1 = Monday .. 7 = Sunday) or English day names;
+    omitted means every day. The weekday is read on the calendar named by the block's
+    weekday_timezone.
+    """
+
+    hours_utc: ReadOnly[str | Sequence[str]]
+    weekdays: ReadOnly[Sequence[int | str]]
+
+
+class OffPeakPricing(TypedDict, total=False):
+    """Time-windowed off-peak rates for providers that discount by time of day (e.g. DeepSeek).
+
+    hours_utc is a "HH:MM-HH:MM" string in UTC, or a list of them for multiple daily windows,
+    applying on every day of the week; a window may wrap past midnight. windows adds
+    day-of-week-qualified rules (e.g. weekend-only whole-day off-peak), matched as a union
+    with hours_utc. weekday_timezone names the IANA calendar weekdays are read on, defaulting
+    to UTC. Any rate left unset falls back to the standard rate.
+    """
+
+    hours_utc: ReadOnly[str | Sequence[str]]
+    windows: ReadOnly[Sequence[OffPeakWindow]]
+    weekday_timezone: ReadOnly[str]
+    input_cost_per_token: ReadOnly[float]
+    output_cost_per_token: ReadOnly[float]
+    cache_read_input_token_cost: ReadOnly[float]
+
+
 class ModelInfoBase(ProviderSpecificModelInfo, total=False):
     key: Required[str]  # the key in litellm.model_cost which is returned
 
@@ -225,6 +257,7 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False):
     # Smallest prefix this model will actually cache, whatever caching mechanism its provider uses.
     # Absent means the provider-agnostic default applies; see MINIMUM_PROMPT_CACHE_TOKEN_COUNT.
     prompt_cache_min_tokens: int | None
+    off_peak_pricing: ReadOnly[OffPeakPricing | None]  # time-windowed off-peak rates
     input_cost_per_character: float | None  # only for vertex ai models
     input_cost_per_audio_token: float | None
     input_cost_per_token_above_128k_tokens: float | None  # only for vertex ai models
@@ -3486,17 +3519,22 @@ class CustomPricingLiteLLMParams(MirroredPricingParams):
         return {k: v for k, v in model_info.items() if k not in cls.model_fields}
 
 
-SHARED_BACKEND_MODEL_INFO_FIELDS: Final[frozenset[str]] = frozenset(
-    ModelInfoBase.__required_keys__ | ModelInfoBase.__optional_keys__
-) - frozenset(CustomPricingLiteLLMParams.model_fields)
+DEPLOYMENT_SCOPED_PRICING_FIELDS: Final[frozenset[str]] = frozenset({"off_peak_pricing"})
+
+SHARED_BACKEND_MODEL_INFO_FIELDS: Final[frozenset[str]] = (
+    frozenset(ModelInfoBase.__required_keys__ | ModelInfoBase.__optional_keys__)
+    - frozenset(CustomPricingLiteLLMParams.model_fields)
+    - DEPLOYMENT_SCOPED_PRICING_FIELDS
+)
 
 
 def shared_backend_model_info(model_info: dict[str, Any]) -> dict[str, Any]:
     """Return only the fields safe to register under a shared ``{provider}/{model}``
     key in ``litellm.model_cost``: cost-map schema fields (``ModelInfoBase``) minus
-    per-deployment pricing overrides. Per-deployment metadata (``id``,
-    ``access_via_team_ids``, arbitrary custom keys) never belongs on the shared key;
-    it stays under the deployment's unique model id.
+    per-deployment pricing overrides and deployment-scoped pricing blocks such as
+    ``off_peak_pricing``. Per-deployment metadata (``id``, ``access_via_team_ids``,
+    arbitrary custom keys) never belongs on the shared key; it stays under the
+    deployment's unique model id.
     """
     return {k: v for k, v in model_info.items() if k in SHARED_BACKEND_MODEL_INFO_FIELDS}
 
diff --git a/litellm/utils.py b/litellm/utils.py
index 028682661f7..2fdc4a45148 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -2869,10 +2869,9 @@ def _update_dictionary(existing_dict: dict, new_dict: dict) -> dict:
             elif isinstance(v, dict):
                 existing_nested_dict = existing_dict.get(k)
                 if isinstance(existing_nested_dict, dict):
-                    existing_nested_dict.update(v)
-                    existing_dict[k] = existing_nested_dict
+                    existing_dict[k] = {**existing_nested_dict, **v}  # mutable-ok: copy-on-write merge
                 else:
-                    existing_dict[k] = v
+                    existing_dict[k] = dict(v)  # mutable-ok: detached copy, never the caller's dict by reference
             else:
                 existing_dict[k] = v
 
@@ -5860,6 +5859,7 @@ def _get_model_info_helper(
                 cache_creation_input_token_cost_above_1hr=_model_info.get(
                     "cache_creation_input_token_cost_above_1hr", None
                 ),
+                off_peak_pricing=_model_info.get("off_peak_pricing", None),
                 input_cost_per_character=_model_info.get("input_cost_per_character", None),
                 input_cost_per_token_above_128k_tokens=_model_info.get("input_cost_per_token_above_128k_tokens", None),
                 input_cost_per_token_above_200k_tokens=_model_info.get("input_cost_per_token_above_200k_tokens", None),
diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
index 3c4121977de..0e1c832ebf5 100644
--- a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
+++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
@@ -32,6 +32,8 @@ from litellm.litellm_core_utils.llm_cost_calc.utils import (
     TokenTypeCostBreakdown,
     _calculate_input_cost,
     _get_token_base_cost,
+    _is_off_peak,
+    _is_within_off_peak_window,
     calculate_cache_writing_cost,
     generic_cost_per_token,
     get_token_type_cost_breakdown,
@@ -409,6 +411,377 @@ def test_get_token_base_cost_picks_highest_crossed_tier():
     assert prompt_base_cost == 9e-6
 
 
+def test_is_within_off_peak_window_same_day():
+    from datetime import datetime, timezone
+
+    window = "09:00-17:00"
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 12, 0, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 8, 59, tzinfo=timezone.utc)) is False
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 9, 0, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 17, 0, tzinfo=timezone.utc)) is False
+
+
+def test_is_within_off_peak_window_wraps_midnight():
+    from datetime import datetime, timezone
+
+    window = "16:30-00:30"
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 0, 15, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 16, 30, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 0, 30, tzinfo=timezone.utc)) is False
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 12, 0, tzinfo=timezone.utc)) is False
+
+
+def test_is_within_off_peak_window_equal_start_and_end_covers_whole_day():
+    """An equal start and end is the natural way to spell off-peak all day. It used to take the
+    non-wrap branch, where start <= now < end can never hold, so it matched nothing and billed at
+    standard rates around the clock without raising or logging anything."""
+    from datetime import datetime, timezone
+
+    for window in ("00:00-00:00", "10:00-10:00"):
+        for hour in range(24):
+            assert (
+                _is_within_off_peak_window(window, datetime(2026, 1, 1, hour, 0, tzinfo=timezone.utc)) is True
+            ), f"{window} should cover {hour:02d}:00"
+
+
+def test_is_within_off_peak_window_multiple_windows():
+    from datetime import datetime, timezone
+
+    # Providers like DeepSeek V4 have more than one daily peak/off-peak window.
+    windows = ["01:00-05:00", "13:00-16:00"]
+    assert _is_within_off_peak_window(windows, datetime(2026, 1, 1, 3, 0, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(windows, datetime(2026, 1, 1, 14, 30, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(windows, datetime(2026, 1, 1, 9, 0, tzinfo=timezone.utc)) is False
+    # a malformed entry in the list is ignored, valid entries still match
+    assert _is_within_off_peak_window(["bad", "13:00-16:00"], datetime(2026, 1, 1, 14, 0, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window([], datetime(2026, 1, 1, 14, 0, tzinfo=timezone.utc)) is False
+
+
+def test_is_within_off_peak_window_normalizes_timezone_aware_input():
+    from datetime import datetime, timedelta, timezone
+
+    # A caller may pass a non-UTC aware datetime; the window is UTC and must be
+    # evaluated in UTC, not against the caller's wall-clock. 09:00 at UTC+8 is
+    # 01:00 UTC, inside the 01:00-05:00 window.
+    tz_plus_8 = timezone(timedelta(hours=8))
+    assert _is_within_off_peak_window("01:00-05:00", datetime(2026, 1, 1, 9, 0, tzinfo=tz_plus_8)) is True
+    assert _is_within_off_peak_window("01:00-05:00", datetime(2026, 1, 1, 12, 0, tzinfo=tz_plus_8)) is True
+    # 06:00 at UTC+8 is 22:00 UTC the previous day, outside the window
+    assert _is_within_off_peak_window("01:00-05:00", datetime(2026, 1, 1, 6, 0, tzinfo=tz_plus_8)) is False
+
+
+def test_is_within_off_peak_window_malformed_returns_false():
+    from datetime import datetime, timezone
+
+    now = datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc)
+    assert _is_within_off_peak_window("not-a-window", now) is False
+    assert _is_within_off_peak_window("16:30", now) is False
+    assert _is_within_off_peak_window("25:00-26:00", now) is False
+
+
+def test_is_off_peak_weekday_qualified_windows_deepseek_schedule():
+    """DeepSeek since 2026-08-23: peak is 01:00-04:00 and 06:00-10:00 UTC on weekdays only, with
+    weekends off-peak around the clock. The weekday axis is not a filter on one window set; on
+    two days of seven the off-peak window becomes the whole day, so the schedule needs two
+    day-qualified rules. The weekend instants inside would-be peak hours are the ones a
+    time-only implementation bills wrong."""
+    from datetime import datetime, timezone
+
+    deepseek = {
+        "windows": [
+            {"hours_utc": ["00:00-01:00", "04:00-06:00", "10:00-00:00"], "weekdays": [1, 2, 3, 4, 5]},
+            {"hours_utc": "00:00-00:00", "weekdays": [6, 7]},
+        ],
+    }
+    peak_instants = [
+        datetime(2026, 8, 24, 1, 30, tzinfo=timezone.utc),
+        datetime(2026, 8, 26, 7, 0, tzinfo=timezone.utc),
+        datetime(2026, 8, 28, 9, 59, tzinfo=timezone.utc),
+    ]
+    off_peak_instants = [
+        datetime(2026, 8, 23, 1, 30, tzinfo=timezone.utc),
+        datetime(2026, 8, 29, 2, 0, tzinfo=timezone.utc),
+        datetime(2026, 8, 30, 8, 0, tzinfo=timezone.utc),
+        datetime(2026, 8, 26, 5, 0, tzinfo=timezone.utc),
+        datetime(2026, 8, 28, 16, 30, tzinfo=timezone.utc),
+        datetime(2026, 8, 24, 0, 30, tzinfo=timezone.utc),
+    ]
+    for when in peak_instants:
+        assert _is_off_peak(deepseek, when) is False, f"{when.isoformat()} should bill peak"
+    for when in off_peak_instants:
+        assert _is_off_peak(deepseek, when) is True, f"{when.isoformat()} should bill off-peak"
+
+
+def test_is_off_peak_weekday_timezone_reads_vendor_calendar():
+    """The UTC and Asia/Shanghai calendars only disagree about the date over 16:00-24:00 UTC, so
+    a window in that stretch is the one place a vendor-local weekday differs from a UTC one:
+    2026-08-28T16:30Z is Friday in UTC but already Saturday in Beijing."""
+    from datetime import datetime, timezone
+
+    shanghai_saturday = {
+        "weekday_timezone": "Asia/Shanghai",
+        "windows": [{"hours_utc": "16:00-17:00", "weekdays": [6]}],
+    }
+    assert _is_off_peak(shanghai_saturday, datetime(2026, 8, 28, 16, 30, tzinfo=timezone.utc)) is True
+    assert _is_off_peak(shanghai_saturday, datetime(2026, 8, 29, 16, 30, tzinfo=timezone.utc)) is False
+
+
+def test_is_off_peak_weekdays_default_utc_calendar_and_accept_names():
+    from datetime import datetime, timezone
+
+    named_weekend = {"windows": [{"hours_utc": "00:00-00:00", "weekdays": ["Sat", "sunday"]}]}
+    assert _is_off_peak(named_weekend, datetime(2026, 8, 29, 12, 0, tzinfo=timezone.utc)) is True
+    assert _is_off_peak(named_weekend, datetime(2026, 8, 28, 12, 0, tzinfo=timezone.utc)) is False
+
+    utc_friday = {"windows": [{"hours_utc": "16:00-17:00", "weekdays": [5]}]}
+    assert _is_off_peak(utc_friday, datetime(2026, 8, 28, 16, 30, tzinfo=timezone.utc)) is True
+    assert _is_off_peak(utc_friday, datetime(2026, 8, 29, 16, 30, tzinfo=timezone.utc)) is False
+
+
+def test_is_off_peak_naive_current_time_read_as_utc():
+    from datetime import datetime
+
+    block = {"windows": [{"hours_utc": "16:00-17:00", "weekdays": [5]}]}
+    assert _is_off_peak(block, datetime(2026, 8, 28, 16, 30)) is True
+    assert _is_off_peak(block, datetime(2026, 8, 29, 16, 30)) is False
+
+
+def test_is_off_peak_invalid_weekday_timezone_falls_back_to_utc():
+    from datetime import datetime, timezone
+
+    block = {"weekday_timezone": "Not/AZone", "windows": [{"hours_utc": "16:00-17:00", "weekdays": [5]}]}
+    assert _is_off_peak(block, datetime(2026, 8, 28, 16, 30, tzinfo=timezone.utc)) is True
+    assert _is_off_peak(block, datetime(2026, 8, 29, 16, 30, tzinfo=timezone.utc)) is False
+
+
+def test_is_off_peak_ignores_malformed_weekday_rules():
+    from datetime import datetime, timezone
+
+    when = datetime(2026, 8, 29, 12, 0, tzinfo=timezone.utc)
+    assert _is_off_peak({"windows": [{"hours_utc": "00:00-00:00", "weekdays": []}]}, when) is False
+    assert _is_off_peak({"windows": [{"hours_utc": "00:00-00:00", "weekdays": [0, 8, "noday", True]}]}, when) is False
+    assert _is_off_peak({"windows": [{"weekdays": [6]}]}, when) is False
+    assert _is_off_peak({"windows": [{"hours_utc": 1630}]}, when) is False
+    assert _is_off_peak({"windows": ["00:00-00:00"]}, when) is False
+    assert _is_off_peak({"windows": "00:00-00:00"}, when) is False
+    assert _is_off_peak({"hours_utc": 1630}, when) is False
+    assert _is_off_peak({}, when) is False
+
+
+def test_is_off_peak_flat_hours_and_windows_are_a_union():
+    from datetime import datetime, timezone
+
+    block = {
+        "hours_utc": "04:00-06:00",
+        "windows": [{"hours_utc": "00:00-00:00", "weekdays": [7]}],
+    }
+    assert _is_off_peak(block, datetime(2026, 8, 28, 5, 0, tzinfo=timezone.utc)) is True
+    assert _is_off_peak(block, datetime(2026, 8, 30, 20, 0, tzinfo=timezone.utc)) is True
+    assert _is_off_peak(block, datetime(2026, 8, 28, 20, 0, tzinfo=timezone.utc)) is False
+
+
+def test_get_token_base_cost_weekend_only_off_peak_rate():
+    from datetime import datetime, timezone
+    from typing import cast
+
+    from litellm.types.utils import ModelInfo
+
+    model_info = cast(
+        ModelInfo,
+        {
+            "input_cost_per_token": 1e-6,
+            "output_cost_per_token": 2e-6,
+            "off_peak_pricing": {
+                "windows": [
+                    {"hours_utc": ["00:00-01:00", "04:00-06:00", "10:00-00:00"], "weekdays": [1, 2, 3, 4, 5]},
+                    {"hours_utc": "00:00-00:00", "weekdays": [6, 7]},
+                ],
+                "input_cost_per_token": 5e-7,
+                "output_cost_per_token": 1e-6,
+            },
+        },
+    )
+    usage = Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150)
+
+    saturday_peak_hours = _get_token_base_cost(
+        model_info, usage, current_time=datetime(2026, 8, 29, 2, 0, tzinfo=timezone.utc)
+    )
+    assert saturday_peak_hours[:2] == (5e-7, 1e-6)
+
+    monday_same_hours = _get_token_base_cost(
+        model_info, usage, current_time=datetime(2026, 8, 24, 2, 0, tzinfo=timezone.utc)
+    )
+    assert monday_same_hours[:2] == (1e-6, 2e-6)
+
+
+def test_get_token_base_cost_applies_off_peak_pricing():
+    from datetime import datetime, timezone
+    from typing import cast
+
+    from litellm.types.utils import ModelInfo
+
+    model_info = cast(
+        ModelInfo,
+        {
+            "input_cost_per_token": 1e-6,
+            "output_cost_per_token": 2e-6,
+            "cache_read_input_token_cost": 1e-7,
+            "off_peak_pricing": {
+                "hours_utc": "16:30-00:30",
+                "input_cost_per_token": 5e-7,
+                "output_cost_per_token": 1e-6,
+                "cache_read_input_token_cost": 5e-8,
+            },
+        },
+    )
+    usage = Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150)
+
+    off_peak = _get_token_base_cost(model_info, usage, current_time=datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc))
+    assert off_peak[0] == 5e-7
+    assert off_peak[1] == 1e-6
+    assert off_peak[4] == 5e-8
+
+    peak = _get_token_base_cost(model_info, usage, current_time=datetime(2026, 1, 1, 12, 0, tzinfo=timezone.utc))
+    assert peak[0] == 1e-6
+    assert peak[1] == 2e-6
+    assert peak[4] == 1e-7
+
+
+def test_get_token_base_cost_non_mapping_off_peak_block_bills_standard_rates():
+    """A truthy non-mapping off_peak_pricing value (a bare string or a list in
+    YAML) must bill standard rates rather than raising, matching how every
+    other malformed piece of the block behaves.
+    """
+    from datetime import datetime, timezone
+    from typing import cast
+
+    from litellm.types.utils import ModelInfo
+
+    usage = Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150)
+    when = datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc)
+
+    for malformed_block in ("16:00-19:00", ["16:00-19:00"], 5e-7, True):
+        model_info = cast(
+            ModelInfo,
+            {
+                "input_cost_per_token": 1e-6,
+                "output_cost_per_token": 2e-6,
+                "off_peak_pricing": malformed_block,
+            },
+        )
+        result = _get_token_base_cost(model_info, usage, current_time=when)
+        assert result[0] == 1e-6
+        assert result[1] == 2e-6
+
+
+def test_get_token_base_cost_off_peak_falls_back_to_standard_when_unset():
+    from datetime import datetime, timezone
+    from typing import cast
+
+    from litellm.types.utils import ModelInfo
+
+    model_info = cast(
+        ModelInfo,
+        {
+            "input_cost_per_token": 1e-6,
+            "output_cost_per_token": 2e-6,
+            "off_peak_pricing": {"hours_utc": "16:30-00:30", "input_cost_per_token": 5e-7},
+        },
+    )
+    usage = Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150)
+
+    result = _get_token_base_cost(model_info, usage, current_time=datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc))
+    assert result[0] == 5e-7
+    assert result[1] == 2e-6
+
+
+def test_get_token_base_cost_off_peak_wins_over_threshold():
+    from datetime import datetime, timezone
+    from typing import cast
+
+    from litellm.types.utils import ModelInfo
+
+    model_info = cast(
+        ModelInfo,
+        {
+            "input_cost_per_token": 1e-6,
+            "output_cost_per_token": 2e-6,
+            "input_cost_per_token_above_200k_tokens": 3e-6,
+            "output_cost_per_token_above_200k_tokens": 4e-6,
+            "off_peak_pricing": {
+                "hours_utc": "16:30-00:30",
+                "input_cost_per_token": 5e-7,
+                "output_cost_per_token": 1e-6,
+            },
+        },
+    )
+    usage = Usage(prompt_tokens=250000, completion_tokens=250000, total_tokens=500000)
+
+    off_peak = _get_token_base_cost(model_info, usage, current_time=datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc))
+    assert off_peak[0] == 5e-7
+    assert off_peak[1] == 1e-6
+
+    peak = _get_token_base_cost(model_info, usage, current_time=datetime(2026, 1, 1, 12, 0, tzinfo=timezone.utc))
+    assert peak[0] == 3e-6
+    assert peak[1] == 4e-6
+
+
+def test_get_model_info_propagates_off_peak_fields():
+    model_name = "test-off-peak-model"
+    off_peak_pricing = {
+        "hours_utc": "16:30-00:30",
+        "input_cost_per_token": 5e-7,
+        "output_cost_per_token": 1e-6,
+        "cache_read_input_token_cost": 5e-8,
+    }
+    litellm.register_model(
+        {
+            model_name: {
+                "litellm_provider": "openai",
+                "mode": "chat",
+                "input_cost_per_token": 1e-6,
+                "output_cost_per_token": 2e-6,
+                "off_peak_pricing": off_peak_pricing,
+            }
+        }
+    )
+    info = litellm.get_model_info(model=model_name)
+    assert info["off_peak_pricing"] == off_peak_pricing
+
+
+def test_get_token_base_cost_off_peak_wins_over_tiered_pricing():
+    """Tiered pricing resolves base rates on its own path and returns early, so off-peak has to
+    be applied there too or a model carrying both would silently bill the tier rate all day."""
+    from datetime import datetime, timezone
+
+    model_name = "litellm-test-off-peak-tiered"
+    litellm.register_model(
+        {
+            model_name: {
+                "litellm_provider": "openai",
+                "mode": "chat",
+                "tiered_pricing": [
+                    {"range": [0, 128000], "input_cost_per_token": 3e-6, "output_cost_per_token": 6e-6},
+                ],
+                "off_peak_pricing": {
+                    "hours_utc": "16:30-00:30",
+                    "input_cost_per_token": 5e-7,
+                    "output_cost_per_token": 1e-6,
+                },
+            }
+        }
+    )
+    info = litellm.get_model_info(model=model_name)
+    usage = Usage(prompt_tokens=1_000, completion_tokens=100, total_tokens=1_100)
+
+    inside = _get_token_base_cost(info, usage, current_time=datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc))
+    assert inside[:2] == (5e-7, 1e-6)
+
+    outside = _get_token_base_cost(info, usage, current_time=datetime(2026, 1, 1, 12, 0, tzinfo=timezone.utc))
+    assert outside[:2] == (3e-6, 6e-6)
+
+
 def test_generic_cost_per_token_gpt54_above_272k_tokens(_local_model_cost_map):
     """GPT-5.4/5.4-pro: prompts >272K input tokens priced at 2x input, 1.5x output."""
     model = "gpt-5.4"
diff --git a/tests/test_litellm/test_register_model_custom_pricing.py b/tests/test_litellm/test_register_model_custom_pricing.py
index 39f498b4e58..452a15334ef 100644
--- a/tests/test_litellm/test_register_model_custom_pricing.py
+++ b/tests/test_litellm/test_register_model_custom_pricing.py
@@ -793,3 +793,203 @@ def test_embedding_direct_sdk_custom_pricing_still_registers_shared_key():
     finally:
         litellm.model_cost.pop(model_key, None)
         _invalidate_model_cost_lowercase_map()
+
+
+def test_update_dictionary_merges_nested_dicts_without_aliasing():
+    """A nested dict must be merged copy-on-write: the pre-existing nested dict
+    object stays untouched, and the caller's incoming nested dict is never
+    inserted by reference into the merged result.
+    """
+    from litellm.utils import _update_dictionary
+
+    existing_nested = {"hours_utc": "01:00-02:00"}
+    existing = {"off_peak_pricing": existing_nested}
+    incoming_nested = {"windows": [{"hours_utc": "16:00-19:00", "weekdays": [2]}]}
+    incoming = {"off_peak_pricing": incoming_nested}
+
+    merged = _update_dictionary(existing, incoming)
+
+    assert merged["off_peak_pricing"] == {
+        "hours_utc": "01:00-02:00",
+        "windows": [{"hours_utc": "16:00-19:00", "weekdays": [2]}],
+    }
+    assert existing_nested == {"hours_utc": "01:00-02:00"}
+    assert merged["off_peak_pricing"] is not incoming_nested
+
+    fresh = _update_dictionary({}, incoming)
+    assert fresh["off_peak_pricing"] == incoming_nested
+    assert fresh["off_peak_pricing"] is not incoming_nested
+
+
+def test_router_deployments_sharing_backend_keep_their_own_off_peak_pricing():
+    """Two deployments of the same backend model with different
+    ``off_peak_pricing`` blocks must each keep their own schedule under their
+    unique model id, and neither block may leak onto the shared backend keys.
+
+    Before the fix, ``register_model`` inserted the first deployment's block by
+    reference into the built-in ``gpt-4o-mini`` entry, and the second
+    deployment's registration merged its keys into that same object, corrupting
+    the first deployment's schedule and polluting the built-in entry.
+    """
+    from litellm import Router
+
+    active_block = {
+        "windows": [{"hours_utc": "16:00-19:00", "weekdays": [2]}],
+        "input_cost_per_token": 5e-07,
+        "output_cost_per_token": 1e-06,
+    }
+    inactive_block = {
+        "hours_utc": "05:00-06:00",
+        "input_cost_per_token": 5e-07,
+        "output_cost_per_token": 1e-06,
+    }
+    shared_keys = ["gpt-4o-mini", "openai/gpt-4o-mini"]
+    deployment_ids = ["offpeak-alias-dep-1", "offpeak-alias-dep-2"]
+    original_entries = _snapshot_model_cost_entries(shared_keys)
+
+    router = Router(
+        model_list=[
+            {
+                "model_name": "offpeak-active-weekday",
+                "litellm_params": {
+                    "model": "openai/gpt-4o-mini",
+                    "api_key": "fake-key-for-registration",
+                },
+                "model_info": {
+                    "id": deployment_ids[0],
+                    "input_cost_per_token": 1e-06,
+                    "output_cost_per_token": 2e-06,
+                    "off_peak_pricing": dict(active_block),
+                },
+            },
+            {
+                "model_name": "offpeak-inactive-hours",
+                "litellm_params": {
+                    "model": "openai/gpt-4o-mini",
+                    "api_key": "fake-key-for-registration",
+                },
+                "model_info": {
+                    "id": deployment_ids[1],
+                    "input_cost_per_token": 1e-06,
+                    "output_cost_per_token": 2e-06,
+                    "off_peak_pricing": dict(inactive_block),
+                },
+            },
+        ]
+    )
+
+    try:
+        registered_first = litellm.model_cost[deployment_ids[0]]["off_peak_pricing"]
+        registered_second = litellm.model_cost[deployment_ids[1]]["off_peak_pricing"]
+        assert registered_first == active_block
+        assert registered_second == inactive_block
+        for shared_key in shared_keys:
+            shared_entry = litellm.model_cost.get(shared_key) or {}
+            assert not shared_entry.get("off_peak_pricing")
+    finally:
+        for deployment_id in deployment_ids:
+            litellm.model_cost.pop(deployment_id, None)
+        _restore_model_cost_entries(original_entries)
+        del router
+
+
+def test_router_off_peak_only_deployment_inherits_builtin_base_rates():
+    """A deployment that sets only ``off_peak_pricing`` on its model_info must
+    still be costed from its deployment-scoped entry: the base token rates are
+    inherited from the backend model's built-in cost map entry, since the
+    shared backend key deliberately never carries the off-peak block.
+    """
+    from litellm import Router
+
+    block = {
+        "hours_utc": "00:00-00:00",
+        "input_cost_per_token": 5e-05,
+        "output_cost_per_token": 1e-04,
+    }
+    shared_keys = ["gpt-4o-mini", "openai/gpt-4o-mini"]
+    deployment_id = "offpeak-only-dep-1"
+    original_entries = _snapshot_model_cost_entries(shared_keys + [deployment_id])
+    builtin_info = litellm.get_model_info(model="openai/gpt-4o-mini")
+
+    router = Router(
+        model_list=[
+            {
+                "model_name": "offpeak-only",
+                "litellm_params": {
+                    "model": "openai/gpt-4o-mini",
+                    "api_key": "fake-key-for-registration",
+                },
+                "model_info": {"id": deployment_id, "off_peak_pricing": dict(block)},
+            }
+        ]
+    )
+
+    try:
+        entry = litellm.model_cost[deployment_id]
+        assert entry["off_peak_pricing"] == block
+        assert entry["input_cost_per_token"] is not None
+        assert entry["input_cost_per_token"] == builtin_info["input_cost_per_token"]
+        assert entry["output_cost_per_token"] == builtin_info["output_cost_per_token"]
+        for shared_key in shared_keys:
+            shared_entry = litellm.model_cost.get(shared_key) or {}
+            assert not shared_entry.get("off_peak_pricing")
+    finally:
+        _restore_model_cost_entries(original_entries)
+        del router
+
+
+def test_use_custom_pricing_for_model_sees_off_peak_only_model_info():
+    from litellm.litellm_core_utils.litellm_logging import use_custom_pricing_for_model
+
+    block = {"hours_utc": "00:00-00:00", "input_cost_per_token": 5e-05}
+    assert use_custom_pricing_for_model({"metadata": {"model_info": {"off_peak_pricing": block}}}) is True
+    assert use_custom_pricing_for_model({"metadata": {"model_info": {"off_peak_pricing": None}}}) is False
+    assert use_custom_pricing_for_model({"metadata": {"model_info": {"id": "some-id"}}}) is False
+
+
+def test_completion_cost_applies_off_peak_only_deployment_pricing():
+    """End to end through the cost calculator: with ``custom_pricing`` set and
+    a ``router_model_id`` whose entry carries only an always-on off-peak block,
+    the request bills at the block's rates rather than the shared backend rate.
+    """
+    from litellm import Router
+    from litellm.types.utils import ModelResponse, Usage
+
+    block = {
+        "hours_utc": "00:00-00:00",
+        "input_cost_per_token": 5e-05,
+        "output_cost_per_token": 1e-04,
+    }
+    shared_keys = ["gpt-4o-mini", "openai/gpt-4o-mini"]
+    deployment_id = "offpeak-only-dep-2"
+    original_entries = _snapshot_model_cost_entries(shared_keys + [deployment_id])
+
+    router = Router(
+        model_list=[
+            {
+                "model_name": "offpeak-only",
+                "litellm_params": {
+                    "model": "openai/gpt-4o-mini",
+                    "api_key": "fake-key-for-registration",
+                },
+                "model_info": {"id": deployment_id, "off_peak_pricing": dict(block)},
+            }
+        ]
+    )
+
+    try:
+        response = ModelResponse(
+            model="gpt-4o-mini",
+            usage=Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150),
+        )
+        cost = litellm.completion_cost(
+            completion_response=response,
+            model="openai/gpt-4o-mini",
+            custom_llm_provider="openai",
+            custom_pricing=True,
+            router_model_id=deployment_id,
+        )
+        assert cost == pytest.approx(100 * 5e-05 + 50 * 1e-04)
+    finally:
+        _restore_model_cost_entries(original_entries)
+        del router
diff --git a/tests/test_litellm/test_router_model_cost_isolation.py b/tests/test_litellm/test_router_model_cost_isolation.py
index b580b03574e..7b7a962bf00 100644
--- a/tests/test_litellm/test_router_model_cost_isolation.py
+++ b/tests/test_litellm/test_router_model_cost_isolation.py
@@ -538,6 +538,157 @@ def test_inherit_builtin_cache_pricing_noop_for_unknown_backend():
     assert model_info == {"input_cost_per_token": 0.000003}
 
 
+def test_inherit_builtin_base_rates_for_off_peak_fills_missing_rates():
+    """Direct unit test of the helper: an entry carrying only an
+    off_peak_pricing block inherits the backend model's built-in base token
+    rates, so cost lookup via the deployment id can bill standard rates
+    outside the windows.
+    """
+    backend_model = "gpt-4o-mini"
+    builtin_info = litellm.get_model_info(model=backend_model, custom_llm_provider="openai")
+    off_peak_block = {
+        "hours_utc": "00:00-00:00",
+        "input_cost_per_token": 5e-07,
+        "output_cost_per_token": 1e-06,
+    }
+    model_info = {"off_peak_pricing": off_peak_block}
+
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=model_info,
+        backend_model=backend_model,
+        custom_llm_provider="openai",
+    )
+
+    assert model_info["input_cost_per_token"] == builtin_info["input_cost_per_token"]
+    assert model_info["output_cost_per_token"] == builtin_info["output_cost_per_token"]
+    assert model_info["off_peak_pricing"] == off_peak_block
+
+
+def test_inherit_builtin_base_rates_for_off_peak_carries_threshold_rates():
+    """A backend with above-threshold pricing hands the whole rate structure to
+    the deployment entry, so peak-hour billing of large prompts through that
+    entry matches the shared backend entry instead of flattening to the base
+    rate.
+    """
+    backend_model = "gemini/gemini-2.5-pro"
+    builtin_info = litellm.get_model_info(model=backend_model)
+    assert builtin_info["input_cost_per_token_above_200k_tokens"] is not None
+
+    model_info = {
+        "off_peak_pricing": {"hours_utc": "00:00-00:00", "input_cost_per_token": 5e-07},
+    }
+
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=model_info,
+        backend_model=backend_model,
+        custom_llm_provider="gemini",
+    )
+
+    assert model_info["input_cost_per_token"] == builtin_info["input_cost_per_token"]
+    assert (
+        model_info["input_cost_per_token_above_200k_tokens"]
+        == builtin_info["input_cost_per_token_above_200k_tokens"]
+    )
+    assert (
+        model_info["output_cost_per_token_above_200k_tokens"]
+        == builtin_info["output_cost_per_token_above_200k_tokens"]
+    )
+
+
+def test_inherit_builtin_base_rates_for_off_peak_carries_companion_billing_fields():
+    """Billing rules that are not literal cost rates, like the web search
+    billing unit, must ride along, or grounding and regional uplifts would
+    bill differently through the deployment entry than through the shared
+    backend entry.
+    """
+    backend_model = "gemini-3-pro-image"
+    raw_entry = litellm.model_cost[backend_model]
+    assert raw_entry.get("web_search_billing_unit") is not None
+
+    model_info = {
+        "off_peak_pricing": {"hours_utc": "00:00-00:00", "input_cost_per_token": 5e-07},
+    }
+
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=model_info,
+        backend_model=backend_model,
+        custom_llm_provider=None,
+    )
+
+    assert model_info["web_search_billing_unit"] == raw_entry["web_search_billing_unit"]
+    assert model_info["input_cost_per_token"] == raw_entry["input_cost_per_token"]
+
+
+def test_inherit_builtin_base_rates_for_off_peak_tiered_only_backend_stores_no_zero():
+    """A tiered-only backend has no flat token rates; get_model_info synthesizes
+    zeros for them, and storing those would mark the deployment explicitly
+    priced free. The tier table itself must carry over as an isolated copy so
+    mutating the deployment entry never touches the shared cost map.
+    """
+    backend_model = "dashscope/qwen-flash"
+    raw_tiers = litellm.model_cost[backend_model]["tiered_pricing"]
+
+    model_info = {
+        "off_peak_pricing": {"hours_utc": "00:00-00:00", "input_cost_per_token": 5e-07},
+    }
+
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=model_info,
+        backend_model=backend_model,
+        custom_llm_provider="dashscope",
+    )
+
+    assert model_info.get("input_cost_per_token") != 0
+    assert model_info.get("output_cost_per_token") != 0
+    assert model_info["tiered_pricing"] == raw_tiers
+    assert model_info["tiered_pricing"] is not raw_tiers
+    assert model_info["tiered_pricing"][0] is not raw_tiers[0]
+
+    original_first_tier = copy.deepcopy(raw_tiers[0])
+    model_info["tiered_pricing"][0]["input_cost_per_token"] = 123.0
+    assert raw_tiers[0] == original_first_tier
+
+
+def test_inherit_builtin_base_rates_for_off_peak_leaves_explicit_rates_alone():
+    """An entry that sets its own base rate beside the block already counts as
+    a full custom pricing entry; the helper must not mix builtin rates into it.
+    """
+    model_info = {
+        "off_peak_pricing": {"hours_utc": "00:00-00:00", "input_cost_per_token": 5e-07},
+        "input_cost_per_token": 3e-06,
+    }
+
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=model_info,
+        backend_model="gpt-4o-mini",
+        custom_llm_provider="openai",
+    )
+
+    assert model_info["input_cost_per_token"] == 3e-06
+    assert "output_cost_per_token" not in model_info
+
+
+def test_inherit_builtin_base_rates_for_off_peak_noop_without_block_or_backend():
+    """Nothing happens without an off_peak_pricing block, and an unmapped
+    backend model leaves the entry unchanged rather than raising.
+    """
+    plain_info = {"id": "dep-1"}
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=plain_info,
+        backend_model="gpt-4o-mini",
+        custom_llm_provider="openai",
+    )
+    assert plain_info == {"id": "dep-1"}
+
+    off_peak_info = {"off_peak_pricing": {"hours_utc": "00:00-00:00", "input_cost_per_token": 5e-07}}
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=off_peak_info,
+        backend_model="this-backend-model-does-not-exist-x9y8z7",
+        custom_llm_provider=None,
+    )
+    assert "input_cost_per_token" not in off_peak_info
+
+
 def test_custom_pricing_field_denylist_covers_all_builtin_pricing_fields():
     """The shared-backend-key stripping in Router relies on
     CustomPricingLiteLLMParams enumerating every per-deployment pricing field.