fetch-foundation-model-pricing

name	fetch-foundation-model-pricing
description	Fetch live per-token, per-image, and per-GPU-hour prices for foundation models across Anthropic, OpenAI, Google, AWS Bedrock, Azure OpenAI, OCI Generative AI, and Vertex AI. Supports single-model lookup and comparative multi-provider tables. Every price is labeled with source URL and ISO 8601 fetch timestamp. No credentials accepted.
allowed-tools	Read Grep Glob WebFetch
metadata	{"author":"github: Raishin","version":"0.1.1","updated":"2026-05-13","category":"finops","lifecycle":"experimental"}

Fetch Foundation Model Pricing

Purpose

Retrieve current public pricing for foundation models across the major AI/cloud providers and return structured, provenance-labeled output. Supports two modes:

• Single-model lookup: fetch the current price for a specific model and deployment target (e.g., Claude Sonnet 4.5 on Anthropic direct, or on Bedrock).
• Comparative table: build a side-by-side price comparison across two or more models or providers for the same task type (text, image, embedding, or GPU-hour).

When to use

Use this skill when:

• The user asks "how much does model X cost per token / per image / per GPU-hour"
• The user wants to compare inference costs across two or more providers for the same model family or equivalent capability tier
• The user needs to estimate monthly AI inference spend given a volume projection
• The user wants to understand how context caching or batch pricing changes the effective cost curve
• The user wants a FOCUS-aware cost breakdown (BilledCost, EffectiveCost) for AI inference line items

Operating rules

• Fetch live prices first. Use WebFetch to retrieve prices from each provider's public pricing page before relying on any internal knowledge. AI model pricing changes frequently; stale numbers mislead.
• Label every price. Each price value must carry exactly one provenance label:
  • live-price — fetched from a provider's public pricing page or API within this session; include source URL and ISO 8601 timestamp.
  • documentation-based — sourced from official documentation when a live fetch was not possible; note the documentation URL and its visible publication date.
  • assumed — derived from an analogous model or tier when no direct published price exists; state the assumption explicitly.
  • excluded — pricing that exists but was intentionally omitted from the output; state why.
• Include source URL and timestamp. For every live-price value, state the exact URL fetched and the UTC timestamp of the fetch to the minute (e.g., 2026-05-13T14:32Z).
• On-demand pricing only unless told otherwise. Do not apply reserved capacity, committed use, or enterprise negotiated pricing unless the user explicitly requests it.
• No credentials required or accepted. All provider pricing pages are public and unauthenticated. Never ask for API keys, billing account IDs, or tenant-specific data.
• FOCUS column mapping. Where a cost estimate is produced, note the corresponding FOCUS v1.2 columns: BilledCost (what the provider charges), EffectiveCost (after credits or discounts), ServiceCategory (AI and Machine Learning), ChargeCategory (Usage), SkuId (model ID + deployment tier), SkuPriceId (price dimension: input-token / output-token / cached-token / image / gpu-hour).
• Load references only when needed.

Pricing dimensions

Dimension	Unit	Applies to
Input tokens	per 1M tokens	All text models
Output tokens	per 1M tokens	All text models
Cached input tokens	per 1M tokens	Models with context caching (Anthropic, Gemini, Bedrock)
Batch input tokens	per 1M tokens	Models with async batch mode (Anthropic, OpenAI, Bedrock)
Batch output tokens	per 1M tokens	Models with async batch mode
Images (input)	per image or per 1K images	Multimodal models
GPU-hour	per hour per GPU type	Self-hosted / dedicated endpoints (Vertex AI, Bedrock provisioned throughput, Azure PTU)

Providers in scope

Provider	Deployment target	Reference
Anthropic	Direct API	references/providers.md
OpenAI	Direct API	references/providers.md
Google	Vertex AI	references/providers.md
AWS	Bedrock	references/providers.md
Azure	Azure OpenAI Service	references/providers.md
OCI	Generative AI Service	references/providers.md

Response minimum

Return, at minimum:

• confirmed model name(s), provider(s), and deployment target(s)
• pricing dimensions covered (input, output, cached, batch, image, GPU-hour)
• line-item price table: model | provider | dimension | unit price | provenance label | source URL | fetch timestamp
• for comparative tables: a summary row noting the cheapest and most expensive option per dimension
• key assumptions (on-demand, no reserved/committed pricing, USD unless stated)
• FOCUS column mapping for any cost estimate produced

References

Load these only when needed:

• Provider pricing URLs — public pricing page URLs per provider for live WebFetch.
• Token economics — input/output/cached/batch pricing model, $/M token math, and context caching cost curve.