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9ad1d9a39a
Claude Code resolves to Opus 5 and Sonnet 5 by default, and neither was selectable on a provider record. An operator building a record from the catalog could not authorise the client's own default, so llm_router denied those requests as model_not_routable. Opus 5 carried a supplemental pricing row that priced gateway traffic but never reached the dashboard; Sonnet 5 was absent everywhere, so a request that did route through a catch-all gateway recorded zero cost and under-counted every budget it should have charged. Add both to the Anthropic, Bedrock and Vertex lineups at the published rates, and drop the supplemental rows now that the catalog carries them.
293 lines
8.2 KiB
YAML
293 lines
8.2 KiB
YAML
# Default LLM pricing used by NetBird's Agent Network cost metering.
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# GENERATED from the management catalog — do not edit this file in the
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# repository; regenerate with:
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#
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# go generate ./management/internals/modules/agentnetwork/pricing
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#
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# Operators: copy this file to <datadir>/defaults_llm_pricing.yaml (or
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# any path configured via management.json:
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#
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# { "AgentNetwork": { "PricingDefaultsFile": "/path/defaults_llm_pricing.yaml" } }
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#
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# ) and adjust the entries you want to change. Management re-reads the
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# file periodically (mtime poll, every minute): the live table feeds the
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# proxies' cost metering and the dashboard's model-price prefill, so
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# edits apply without a restart. Your file only needs the entries you
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# want to change — but each entry REPLACES the built-in entry for that
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# surface+model whole, so repeat the cache rates you want to keep.
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# Unknown fields and negative or non-finite rates are rejected: at
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# startup that fails boot (for an explicitly configured path); at
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# runtime the previous table is kept and a warning is logged. Deleting
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# the file reverts to the built-in defaults below.
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#
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# Top-level keys are pricing surfaces — the parser shape requests are
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# metered under: "openai" (also Azure, Mistral, and OpenAI-compatible
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# gateways), "anthropic" (also Anthropic-on-Vertex), "bedrock"
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# (normalized ids, e.g. anthropic.claude-sonnet-4-5). Model keys must be
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# the normalized id the proxy meters (version/region suffixes stripped).
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#
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# Values are USD per 1_000 tokens. Optional cache fields:
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# cached_input_per_1k OpenAI shape: rate for cached prompt tokens
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# (a SUBSET of input tokens). Absent -> cached
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# portion bills at input_per_1k.
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# cache_read_per_1k Anthropic shape: rate for cache_read tokens
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# (ADDITIVE to input). Absent -> input rate.
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# cache_creation_per_1k Anthropic shape: rate for cache_creation
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# tokens (ADDITIVE to input). Absent -> input
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# rate.
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anthropic:
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claude-fable-5:
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input_per_1k: 0.01
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output_per_1k: 0.05
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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-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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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-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-4-7:
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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-4-8:
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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-5:
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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-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-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-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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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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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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bedrock:
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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-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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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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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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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-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-4-7:
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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-4-8:
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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-5:
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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-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-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-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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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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openai:
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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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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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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:
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input_per_1k: 0.0005
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output_per_1k: 0.0015
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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-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:
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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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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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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-5.3-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-5.4:
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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-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-5.4-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-5.5:
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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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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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cache_read_per_1k: 0.0003
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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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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-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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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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mistral-embed:
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input_per_1k: 0.0001
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output_per_1k: 0
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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-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-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-small-latest:
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input_per_1k: 0.00006
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output_per_1k: 0.00018
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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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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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