For enterprise CIOs, CFOs, CAIOs and FinOps leaders

Lower AI cost across the enterprise, inside your governance envelope

We find every AI workload you run, cut what it costs and keep it within your rules, then prove the savings on your real bill. Automated where data allows, partner-led where your knowledge matters.

Book 30 minutes with us →Start with an assessment

What enterprise teams ask us, and what they get

Where is our AI money going?

Every workload, team and vendor priced, with the cost per business outcome.

How do we cut cost without hurting quality?

Each lever priced before you pull it, inside your quality floor.

Are we within our rules?

Approved models by data class, approval gates and an evidence journal.

Can we prove it to finance and audit?

Estimate vs actual on your real bill, every month.

How we do it, step by step

  1. 1Assess

    Read-only collection from your systems plus a short partner questionnaire.

  2. 2See

    Total and granular cost: per workload, team, model and step.

  3. 3Reduce

    Caching, routing, right-sized models and caps, priced and enforced in your gateway.

  4. 4Govern

    Rules you approve run as policy, re-checked on every change.

  5. 5Prove and monitor

    Savings on the real bill; drift starts the next improvement.

Continuous: monitoring, optimization and governance re-run as prices, models and usage change.

Automated where data allows, partner-led where your knowledge matters

Automated data collection

Read-only connectors pull usage, cost and configuration from what you already run. Nothing to install in the request path.

  • Identity and usage: Microsoft Entra, Microsoft Graph, Intune, Copilot
  • AI and cloud: OpenAI, Anthropic, AWS Bedrock, Azure AI Foundry, Google Vertex AI
  • Cloud bills: AWS, Azure, Google Cloud, FOCUS 1.x exports
  • Gateways: LiteLLM, Cloudflare, Kong, Portkey, Azure APIM

Consulting partner with questionnaires

Our team captures what only your company knows, then curates it into the policies the engines enforce.

  • Your policies, risk appetite and data classes
  • Approved vendors, models and regions
  • Workload owners, budgets and business outcomes
  • Review cadence, approvals and audit needs

Built on

120+ decision engines

Cost, assessment and governance engines that price, decide and compile policy.

One price database

A single source of truth for model and cloud prices, so every number agrees.

Works with your FinOps stack

FOCUS exports in and out; Vantage, CloudZero, Flexera and Apptio stay in place.

Your systems of record

Entra, Graph, AWS, Google Cloud, ServiceNow, OneTrust and CRM systems such as Salesforce and Dynamics 365.

The four AICost.ai products, Enterprise edition

1. CostAssessSee every AI workload, its cost and its gaps.Enterprise: Estate review with our experts, 90-day planCostAssess → 2. CostWallStop overspend in the gateway you already run.Enterprise: Runs in your own networkCostWall → 3. CostProtectAI governance: keep every workload within your rules.Enterprise: Governance record and evidence for auditsCostProtect → 4. CostProofSee the savings on your real bill.Enterprise: Chargeback by team, audit exportCostProof →

Enterprise pricing

Enterprise from $4,500 a month, about 25 workloads. Every plan includes all four products.

Start with the $19,500 Enterprise Baseline, credited to Enterprise.

See full pricing →

Talk to us about your AI estate

30 minutes. We bring a priced example of one of your workloads.

Book 30 minutes with us →Start with an assessment
AICost.ai pricing data keeps our calculations accurate across top AI and cloud vendors · last updated 2026-10-24

Methodology

  • All prices are USD per 1 million tokens, current as of 2026-10-24.
  • Vendor-published values have no mark. Inferred/extrapolated values are marked with * and listed below.
  • Batch API discounts are 50% off standard rates across providers that offer Batch mode.
  • Prompt caching discounts vary by provider (typically 80-90% off cached input tokens).
  • Regional data-residency surcharges (Anthropic 1.1x, OpenAI 1.1x, Google regional tiers) are NOT included in base rates.
  • Long-context pricing tiers apply when input exceeds model threshold.
  • Embedding prices are input-only (no output tokens generated).

Primary sources

Last-verified date is the most recent successful daily snapshot (aicost_pricing_snapshots) or, when no snapshot exists yet, the latest successful crawler run (aicost_crawler_runs). 10 of 10 vendors are currently verified. Aggregator services (TokenCost, AI Pricing Guru, etc.) are not listed.

Anthropic
2026-10-24
https://www.anthropic.com/pricing
Daily snapshot since Sep 2023 · 710 days captured
Anthropic Docs
2026-10-24
https://platform.claude.com/docs/en/about-claude/pricing
Daily snapshot since Sep 2023 · 710 days captured
OpenAI
2026-10-24
https://openai.com/api/pricing/
Daily snapshot since Sep 2023 · 711 days captured
Google AI
2026-10-24
https://ai.google.dev/gemini-api/docs/pricing
Daily snapshot since Dec 2023 · 686 days captured
Google Vertex
2026-10-24
https://cloud.google.com/vertex-ai/generative-ai/pricing
Daily snapshot since Dec 2023 · 686 days captured
DeepSeek
2026-10-24
https://api-docs.deepseek.com/quick_start/pricing
Daily snapshot since May 2024 · 625 days captured
xAI
2026-10-24
https://x.ai/api
Daily snapshot since Nov 2024 · 543 days captured
Mistral
2026-10-24
https://mistral.ai/pricing
Daily snapshot since Dec 2023 · 684 days captured
Cohere
2026-10-24
https://cohere.com/pricing
Daily snapshot since Sep 2023 · 710 days captured
Voyage AI
2026-10-24
https://docs.voyageai.com/docs/pricing

Inferred values (marked with * in calculator tables)

Derived from industry conventions, not directly published by the vendor. Typical conventions: cached input = 10% of base (90% off), Batch API = 50% of base (50% off).

Vendor / Model Field Why it’s inferred
Anthropic — Claude Sonnet 4.6 cachedInput Derived at 10% of input rate — Anthropic publishes 90% cache-hit discount on this tier.
Anthropic — Claude Sonnet 4.5 cachedInput Derived at 10% of input rate; same 90% cache-hit convention as Sonnet 4.6.
Anthropic — Claude Sonnet 4.5 batchInput Derived at 50% of standard input — Anthropic documents uniform 50% Batch discount.
Anthropic — Claude Sonnet 4.5 batchOutput Derived at 50% of standard output — Anthropic documents uniform 50% Batch discount.
Anthropic — Claude Haiku 4.5 cachedInput Derived at 10% of input rate — Anthropic 90% cache-hit discount convention.
OpenAI — GPT-5.4 Mini cachedInput Derived at 10% of input — OpenAI documents automatic 90% discount on cache hits across GPT-5.x tier.
OpenAI — GPT-5.4 Nano cachedInput Derived at 10% of input — OpenAI 90% cache-hit convention.
OpenAI — GPT-5.4 Nano batchInput Derived at 50% of input — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.4 Nano batchOutput Derived at 50% of output — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.4 Pro cachedInput Derived at 10% of input — OpenAI 90% cache-hit convention.
OpenAI — GPT-5.4 Pro batchInput Derived at 50% of input — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.4 Pro batchOutput Derived at 50% of output — OpenAI Batch API uniform 50% discount.
OpenAI — GPT-5.2 cachedInput Derived at 10% of input; no residency uplift.
OpenAI — GPT-5.2 batchInput Derived at 50% of input.
OpenAI — GPT-5.2 batchOutput Derived at 50% of output.
OpenAI — GPT-5 cachedInput Derived at 10% of input.
OpenAI — GPT-5 batchInput Derived at 50% of input.
OpenAI — GPT-5 batchOutput Derived at 50% of output.
OpenAI — GPT-5.5 Pro cachedInput Derived at 10% of input — OpenAI does not publish a cached rate for *-pro models; using the family convention.
OpenAI — GPT-5.5 Pro batchInput Derived at 50% of input.
OpenAI — GPT-5.5 Pro batchOutput Derived at 50% of output.
OpenAI — GPT-5.2 Pro cachedInput Derived at 10% of input — pro-tier convention.
OpenAI — GPT-5.2 Pro batchInput Derived at 50% of input.
OpenAI — GPT-5.2 Pro batchOutput Derived at 50% of output.
OpenAI — GPT-5.1 batchInput Derived at 50% of input.
OpenAI — GPT-5.1 batchOutput Derived at 50% of output.
OpenAI — GPT-5 Pro batchInput Derived at 50% of input.
OpenAI — GPT-5 Pro batchOutput Derived at 50% of output.
OpenAI — GPT-5 Nano cachedInput Derived at 10% of input.
OpenAI — GPT-5 Nano batchInput Derived at 50% of input.
OpenAI — GPT-5 Nano batchOutput Derived at 50% of output.
Google — Gemini 3 Flash cachedInput Derived at 10% of input — Google caching discount convention ~90%.
Google — Gemini 3.1 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
Google — Gemini 3.1 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 3.1 Flash-Lite batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
Google — Gemini 2.5 Pro cachedInput Derived at 10% of input.
Google — Gemini 2.5 Flash cachedInput Derived at 10% of input.
Google — Gemini 2.5 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
Google — Gemini 2.5 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 2.5 Flash-Lite batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
xAI — Grok 4 (legacy) cachedInput Extrapolated at 25% of base.

Pricing is cross-verified against the LiteLLM community registry when available. Daily snapshots are kept in aicost_pricing_snapshots; every change is logged to aicost_price_changelog with old & new values for full audit trail. Read the full methodology →