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Vendor Concentration Risk · for procurement + CTOs

What happens if your #1 AI vendor goes down?

Herfindahl concentration score + single-point-of-failure cost + diversification plan. Run it before signing a multi-year commit.

HHI index · 0-10,000 scale Enterprise procurement standard
What this calculator does

How locked-in are you to a single AI vendor? What would migration cost?

Why use it
  • Single-vendor risk becomes business risk above certain spend thresholds
  • Models the cost + disruption of a forced migration

New to this calculator? Start with the ⚡ Playground — a few sliders, instant ballpark. Then switch to the 🧮 Calculator for your exact number.

Two ways to use this: visualize in the Playground, then get your number in the Calculator.

▶Playground A quick, visual way to see which factors move your result the most. Open the playground → ▤Calculator Enter your real workload for a precise result you can apply to your own usage. Go to the calculator →
Vendor Concentration Risk Playground
Drag the sliders for an instant estimate.
How much spend is at risk from vendor lock-in?

Concentrating spend with one vendor exposes you to price shocks and painful switching. Price-shock magnitude fixed at default.

Monthly spend at risk
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Change the input sliders below to see new estimates.

How we got this estimate
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💡At-risk = exposed spend × price-shock risk + a switching-cost penalty scaled by how long migration takes.

Leaning on a single AI vendor is a hidden risk. Enter your stack below to see your concentration and what an outage would cost.

Vendor Concentration Risk Calculator

Enter your exact numbers for a precise result.
📊 Not sure of a value? Fields with a ▾ Typical pill offer broad industry ballparks (sourced typical ranges; Enterprise LLM spend concentration is real: top provider held ~40% of enterprise API spend in 2025 (Menlo). Model-deprecation waves make switching-time the key variable.) so you can move forward now — your result gets more accurate as you replace them with your own measured numbers. Values marked * are rough estimates.
🎮 Interactive Guide & Calculator Playground →
💰 Your current AI spendList each AI vendor and your monthly spend with them.How to choose: Add every vendor with its monthly dollar spend; concentration (HHI) is computed from each vendor share of the total.Read the full guide →
Hint: List your AI vendors and monthly spend; we flag over-reliance on one.

Monthly spend per vendor. Ballpark OK - we just need the ratios.

Load preset
About HHI: The Herfindahl-Hirschman Index is the procurement-industry standard for concentration. Scores: <1,500 = competitive, 1,500-2,500 = moderately concentrated, >2,500 = highly concentrated (regulatory concern in many industries).

Results

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- / 10,000
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Total monthly spend
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Top vendor share
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Vendor count
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If top vendor fails
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monthly at risk

Spend distribution

⚠ Scenario analysis
💡 Diversification plan
    Re-plan your budget → Find alternative vendors → Risk + procurement audit →

    Go deeper

    Our playbooks on cutting this number.

    💰
    Budget Planner
    Allocate across vendors
    🔍
    Model Finder
    Identify backup vendors
    📉
    Token Volatility
    Single-vendor pricing risk
    🏗
    Self-Host Break-even
    The ultimate de-risk option

    Need help using this calculator for your workloads?

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    📖 Data sources & methodology 150 text models · 9 embeddings · 40 vision · 55 audio · 8 vector DBs across 10 vendor pages · last verified 2026-09-11

    Methodology

    • All prices are USD per 1 million tokens, current as of 2026-09-11.
    • 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
    2026-09-11
    https://www.anthropic.com/pricing
    Daily snapshot since Sep 2023 · 675 days captured
    Anthropic Docs
    2026-09-11
    https://platform.claude.com/docs/en/about-claude/pricing
    Daily snapshot since Sep 2023 · 675 days captured
    OpenAI
    2026-09-11
    https://openai.com/api/pricing/
    Daily snapshot since Sep 2023 · 676 days captured
    Google AI
    2026-09-11
    https://ai.google.dev/gemini-api/docs/pricing
    Daily snapshot since Dec 2023 · 651 days captured
    Google Vertex
    2026-09-11
    https://cloud.google.com/vertex-ai/generative-ai/pricing
    Daily snapshot since Dec 2023 · 651 days captured
    DeepSeek
    2026-09-11
    https://api-docs.deepseek.com/quick_start/pricing
    Daily snapshot since May 2024 · 590 days captured
    xAI
    2026-09-11
    https://x.ai/api
    Daily snapshot since Nov 2024 · 508 days captured
    Mistral
    2026-09-11
    https://mistral.ai/pricing
    Daily snapshot since Dec 2023 · 649 days captured
    Cohere
    2026-09-11
    https://cohere.com/pricing
    Daily snapshot since Sep 2023 · 675 days captured
    Voyage AI
    2026-08-11
    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 →