Kimi K3 accepts exactly low, high and max, defaults to max, and always thinks.
The map could not say that: medium and high have no supports_*_reasoning_effort
flag because every other reasoning model takes them, so the ten kimi-k3 entries
carried supports_reasoning alone and resolved to unknown. The dashboard then fell
back to a capability-blind level list that deliberately omits max, which is why a
kimi-k3 tier cannot be set to max thinking today.
Add reasoning_effort_levels, an array key in the shape the map already uses for
supported_endpoints and supported_modalities. Where present it is read first and
wins whole; every other entry keeps answering through the per-level flags,
unchanged. It is deliberately a different name from the computed
ModelGroupInfo.supported_reasoning_efforts, which stays derived from a group's
deployments and is never seeded from one deployment's model_info.
The levels are per entry rather than per model, because the deployments differ:
Moonshot, Together, Fireworks and Azure Foundry all forward the level unchanged
and get the model's own low/high/max, while Perplexity documents a six-value
enum it maps down internally and gets that. The /v1/messages degradation chain
consults the same declaration, so the level the map advertises is the level that
path forwards.
Gemini API Maps-grounded prompts were billed as web search and Vertex AI Maps-grounded prompts were not billed at all. Classify grounding metadata per candidate into web search vs Maps requests, carry a distinct google_maps_grounding_requests usage counter through non-streaming and streaming paths, and price it via the new google_maps_grounding_cost_per_query cost map key with per-query and per-prompt defaults keyed off web_search_billing_unit. Fixes#35906
Regenerate model_prices_and_context_window.schema.json and add the flag to
the inline validator schema in test_utils.py so the new cost-map key passes
validate-model-prices-json and the JSON-valid test.
The cache control hook also runs on litellm.responses() input. On a
GPT-5.6 deployment it wrapped a string-content item into a chat-shaped
{"type": "text"} part, which the Responses API rejects, and it never
marked input_text, input_image or input_file parts, so no breakpoint and
no prompt_cache_options reached the provider. Add the Responses part
types to the eligible block set and translate chat-shaped text parts on
non-assistant items to input_text in
ResponsesAPIRequestUtils.merge_prompt_management_input, which both the
async and the sync prompt management sites go through.
The dialect also fired for any GPT-5.6 name that resolved to provider
openai, including deployments pointed at a custom api_base that does not
understand prompt_cache_breakpoint. Decide it once per request from the
provider, the model map and the resolved api_base (request, then
litellm.api_base, then OPENAI_BASE_URL / OPENAI_API_BASE): only
api.openai.com and *.api.openai.com hosts speak the dialect, a top-level
prompt_cache_options opts a custom target in, and litellm_proxy/ targets
never get it. maybe_seed_default_injection_points takes api_base and
stamps the finished decision on the points as _litellm_openai_dialect so
the sync completion() path, whose hook params do not carry api_base,
honors it; maybe_inject_cache_control takes api_base from the
/v1/messages handler.
Eligibility now comes from a supports_prompt_cache_breakpoint model map
flag on the OpenAI gpt-5.6 entries, exposed through
litellm.utils.supports_prompt_cache_breakpoint, with the GPT version rule
kept only for models the map does not know. The OpenAI dialect no longer
reserves a slot for tool_config points, which OpenAI has no cache block
for, and with_prompt_cache_breakpoint plus the chat bridge helper return
a new block instead of mutating their input.
Price ApplyGuardrail usage units recorded by PR #37225 with a new
bedrock/guardrails entry in the model cost map (regional override via
bedrock/{region}/guardrails), add the per-request guardrail_cost to the
standard logging payload's response_cost and CostBreakdown, surface it in
the x-litellm-response-cost header, and bill blocked requests through the
failure hook so key and team budgets see what AWS bills
