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https://github.com/netbirdio/netbird.git
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4e44210c16
Adds a first-class kimi_api catalog entry so operators can govern Kimi K3 and K2 Thinking traffic through the Agent Network proxy instead of riding the generic custom/vllm entry. ParserID is left empty so the proxy's URL sniffer dispatches both body shapes Moonshot serves on the same host and key: the OpenAI-compatible /v1/chat/completions endpoint and the Anthropic-compatible /anthropic/v1/messages endpoint that Moonshot's official Claude Code setup uses (same pattern as the Bifrost gateway entry). Pricing defaults cover both parser surfaces, including the kimi-k3[1m] model id some Claude Code guides use for the 1M-context alias, so cost metering doesn't silently skip those requests. The dashboard's PROVIDER_CATALOG needs a matching entry (separate repo).
295 lines
9.0 KiB
YAML
295 lines
9.0 KiB
YAML
# Embedded default pricing for llm_observability. Compiled into the proxy
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# binary via go:embed in pricing.go; cost annotation works out of the box
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# without any operator action.
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#
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# Operators override entries by dropping a pricing.yaml into --plugin-data-dir
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# (or whichever basename is given via params.pricing_path). The override file
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# only needs entries the operator wants to change; missing entries fall
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# through to these defaults.
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#
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# Values are USD per 1_000 tokens. Public list prices drift; ship a fresh
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# binary or override individual entries via the override file as needed.
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#
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# Optional cache fields:
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# cached_input_per_1k OpenAI: rate for prompt_tokens_details.cached_tokens
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# (a SUBSET of prompt_tokens). Typically 0.5x input.
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# Absent → cached portion bills at input_per_1k.
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# cache_read_per_1k Anthropic: rate for cache_read_input_tokens
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# (ADDITIVE to input_tokens). Typically 0.1x input.
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# Absent → cache reads bill at input_per_1k.
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# cache_creation_per_1k Anthropic: rate for cache_creation_input_tokens
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# (ADDITIVE to input_tokens). Typically 1.25x input.
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# Absent → cache writes bill at input_per_1k.
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openai:
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# OpenAI + OpenAI-compatible providers (openai_api, azure_openai_api,
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# mistral_api, and the openai-parser gateways) all emit llm.provider="openai",
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# so their models are priced here. Kept in sync with the management catalog;
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# rates cross-checked against LiteLLM model_prices_and_context_window.json.
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# GPT-5.x family — cache reads 10% of input (0.1x).
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gpt-5.5:
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input_per_1k: 0.005
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output_per_1k: 0.03
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cached_input_per_1k: 0.0005
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gpt-5.5-pro:
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input_per_1k: 0.03
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output_per_1k: 0.18
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cached_input_per_1k: 0.003
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gpt-5.4:
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input_per_1k: 0.0025
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output_per_1k: 0.015
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cached_input_per_1k: 0.00025
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gpt-5.4-pro:
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input_per_1k: 0.03
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output_per_1k: 0.18
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cached_input_per_1k: 0.003
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gpt-5.4-mini:
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input_per_1k: 0.00075
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output_per_1k: 0.0045
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cached_input_per_1k: 0.000075
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gpt-5.4-nano:
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input_per_1k: 0.0002
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output_per_1k: 0.00125
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cached_input_per_1k: 0.00002
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gpt-5.3-codex:
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input_per_1k: 0.00175
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output_per_1k: 0.014
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cached_input_per_1k: 0.000175
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gpt-5.3-chat-latest:
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input_per_1k: 0.00175
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output_per_1k: 0.014
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cached_input_per_1k: 0.000175
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# GPT-5 (2025) family — kept for gateway requests using the unsuffixed ids.
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gpt-5:
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input_per_1k: 0.00125
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output_per_1k: 0.01
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cached_input_per_1k: 0.000125
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gpt-5-mini:
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input_per_1k: 0.00025
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output_per_1k: 0.002
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cached_input_per_1k: 0.000025
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gpt-5-nano:
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input_per_1k: 0.00005
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output_per_1k: 0.0004
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cached_input_per_1k: 0.000005
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o4-mini:
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input_per_1k: 0.0011
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output_per_1k: 0.0044
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cached_input_per_1k: 0.000275
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# GPT-4.1 family — cache reads 25% of input.
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gpt-4.1:
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input_per_1k: 0.002
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output_per_1k: 0.008
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cached_input_per_1k: 0.0005
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gpt-4.1-mini:
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input_per_1k: 0.0004
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output_per_1k: 0.0016
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cached_input_per_1k: 0.0001
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gpt-4.1-nano:
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input_per_1k: 0.0001
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output_per_1k: 0.0004
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cached_input_per_1k: 0.000025
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# GPT-4o family — cache reads 50% of input (0.5x).
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gpt-4o:
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input_per_1k: 0.0025
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output_per_1k: 0.01
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cached_input_per_1k: 0.00125
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gpt-4o-mini:
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input_per_1k: 0.00015
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output_per_1k: 0.0006
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cached_input_per_1k: 0.000075
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# Older GPT — no prompt caching.
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gpt-4-turbo:
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input_per_1k: 0.01
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output_per_1k: 0.03
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gpt-3.5-turbo:
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input_per_1k: 0.0005
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output_per_1k: 0.0015
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gpt-35-turbo: # Azure deployment alias of gpt-3.5-turbo
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input_per_1k: 0.0005
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output_per_1k: 0.0015
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# Embeddings — no caching, no output tokens.
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text-embedding-3-large:
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input_per_1k: 0.00013
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output_per_1k: 0
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text-embedding-3-small:
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input_per_1k: 0.00002
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output_per_1k: 0
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# Mistral (mistral_api) — routed via the openai parser; no prompt caching.
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mistral-large-latest:
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input_per_1k: 0.0005
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output_per_1k: 0.0015
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mistral-medium-latest:
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input_per_1k: 0.0004
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output_per_1k: 0.002
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mistral-medium-3-5:
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input_per_1k: 0.0015
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output_per_1k: 0.0075
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mistral-small-latest:
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input_per_1k: 0.00006
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output_per_1k: 0.00018
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magistral-medium-latest:
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input_per_1k: 0.002
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output_per_1k: 0.005
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magistral-small-latest:
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input_per_1k: 0.0005
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output_per_1k: 0.0015
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devstral-medium-latest:
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input_per_1k: 0.0004
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output_per_1k: 0.002
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devstral-small-latest:
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input_per_1k: 0.0001
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output_per_1k: 0.0003
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codestral-2508:
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input_per_1k: 0.0003
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output_per_1k: 0.0009
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codestral-latest:
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input_per_1k: 0.001
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output_per_1k: 0.003
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ministral-3-14b-2512:
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input_per_1k: 0.0002
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output_per_1k: 0.0002
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ministral-8b-latest:
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input_per_1k: 0.00015
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output_per_1k: 0.00015
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ministral-3-3b-2512:
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input_per_1k: 0.0001
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output_per_1k: 0.0001
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mistral-embed:
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input_per_1k: 0.0001
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output_per_1k: 0
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# Kimi / Moonshot AI (kimi_api) — OpenAI-compatible /v1 endpoint. Moonshot
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# reports cache hits OpenAI-style when present; cached input is 10% of
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# input for K3 ($0.30 vs $3.00 per MTok) and $0.15/MTok for K2 Thinking.
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kimi-k3:
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input_per_1k: 0.003
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output_per_1k: 0.015
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cached_input_per_1k: 0.0003
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kimi-k2-thinking:
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input_per_1k: 0.0006
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output_per_1k: 0.0025
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cached_input_per_1k: 0.00015
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anthropic:
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# Claude 4.x family — cache reads ≈10% of input, cache writes ≈125% of input.
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# Pricing source: Anthropic's current published rates per million tokens,
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# divided by 1000 for the per-1k figures stored here.
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claude-fable-5:
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input_per_1k: 0.010
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output_per_1k: 0.050
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cache_read_per_1k: 0.001
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cache_creation_per_1k: 0.0125
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claude-opus-4-8:
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input_per_1k: 0.005
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output_per_1k: 0.025
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cache_read_per_1k: 0.0005
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cache_creation_per_1k: 0.00625
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claude-opus-4-7:
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input_per_1k: 0.005
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output_per_1k: 0.025
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cache_read_per_1k: 0.0005
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cache_creation_per_1k: 0.00625
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claude-opus-4-6:
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input_per_1k: 0.005
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output_per_1k: 0.025
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cache_read_per_1k: 0.0005
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cache_creation_per_1k: 0.00625
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claude-opus-4-1:
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input_per_1k: 0.015
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output_per_1k: 0.075
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cache_read_per_1k: 0.0015
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cache_creation_per_1k: 0.01875
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claude-sonnet-4-6:
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input_per_1k: 0.003
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output_per_1k: 0.015
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cache_read_per_1k: 0.0003
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cache_creation_per_1k: 0.00375
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claude-sonnet-4-5:
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input_per_1k: 0.003
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output_per_1k: 0.015
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cache_read_per_1k: 0.0003
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cache_creation_per_1k: 0.00375
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claude-haiku-4-5:
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input_per_1k: 0.001
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output_per_1k: 0.005
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cache_read_per_1k: 0.0001
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cache_creation_per_1k: 0.00125
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# Kimi / Moonshot AI (kimi_api) via the Anthropic-compatible endpoint
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# (/anthropic/v1/messages — the official Claude Code setup). Same rates
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# as the OpenAI-shape entries above. "kimi-k3[1m]" is the model id some
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# Claude Code guides set for the 1M-context alias; priced identically so
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# cost metering doesn't silently skip those requests.
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kimi-k3:
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input_per_1k: 0.003
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output_per_1k: 0.015
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cache_read_per_1k: 0.0003
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"kimi-k3[1m]":
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input_per_1k: 0.003
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output_per_1k: 0.015
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cache_read_per_1k: 0.0003
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kimi-k2-thinking:
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input_per_1k: 0.0006
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output_per_1k: 0.0025
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cache_read_per_1k: 0.00015
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bedrock:
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# AWS Bedrock model ids, normalised by the request parser (cross-region
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# inference-profile prefix + version/throughput suffix stripped), e.g.
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# eu.anthropic.claude-sonnet-4-5-20250929-v1:0 -> anthropic.claude-sonnet-4-5.
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# Anthropic-on-Bedrock keeps the additive cache buckets (read ≈0.1x input,
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# write ≈1.25x input); Nova / Llama report no cache, so cost is input+output.
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anthropic.claude-opus-4-8:
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input_per_1k: 0.005
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output_per_1k: 0.025
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cache_read_per_1k: 0.0005
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cache_creation_per_1k: 0.00625
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anthropic.claude-opus-4-7:
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input_per_1k: 0.005
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output_per_1k: 0.025
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cache_read_per_1k: 0.0005
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cache_creation_per_1k: 0.00625
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anthropic.claude-opus-4-6:
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input_per_1k: 0.005
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output_per_1k: 0.025
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cache_read_per_1k: 0.0005
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cache_creation_per_1k: 0.00625
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anthropic.claude-opus-4-1:
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input_per_1k: 0.015
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output_per_1k: 0.075
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cache_read_per_1k: 0.0015
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cache_creation_per_1k: 0.01875
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anthropic.claude-sonnet-4-6:
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input_per_1k: 0.003
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output_per_1k: 0.015
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cache_read_per_1k: 0.0003
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cache_creation_per_1k: 0.00375
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anthropic.claude-sonnet-4-5:
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input_per_1k: 0.003
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output_per_1k: 0.015
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cache_read_per_1k: 0.0003
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cache_creation_per_1k: 0.00375
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anthropic.claude-haiku-4-5:
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input_per_1k: 0.001
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output_per_1k: 0.005
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cache_read_per_1k: 0.0001
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cache_creation_per_1k: 0.00125
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meta.llama3-3-70b-instruct:
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input_per_1k: 0.00072
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output_per_1k: 0.00072
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amazon.nova-2-lite:
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input_per_1k: 0.0003
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output_per_1k: 0.0025
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amazon.nova-pro:
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input_per_1k: 0.0008
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output_per_1k: 0.0032
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amazon.nova-lite:
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input_per_1k: 0.00006
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output_per_1k: 0.00024
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amazon.nova-micro:
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input_per_1k: 0.000035
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output_per_1k: 0.00014
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