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AI Currency Converter - Pricing Across 12 Currencies

🚀 Open the calculator

Meet Hannah Schmidt. Procurement Manager at a 400-person German enterprise. "Anthropic and OpenAI quote USD. Our budget is in EUR. What's the real cost in our currency, including FX volatility?"

🔥 FX swing in 2024 added 8% to AI costs without warning.

The story

AI vendor pricing is USD-denominated. Anthropic, OpenAI, Google all bill in USD. Your finance team works in your local currency. Without FX awareness, budgets miss reality by 5-15% per year - sometimes more in volatile periods.

Hannah's German enterprise: $50K USD/mo AI bill. At 0.92 EUR/USD: €46K. At 0.98: €49K. At 0.85: €42.5K. The range across one year is real money - and it's not modeled in most procurement budgets, which assume a single conversion rate.

Three FX strategies for AI procurement. (1) Spot-rate budgeting (current rate × 12) - simple but exposed to FX swings. (2) Forward-rate hedging (lock in for 6-12 months) - pricier but predictable. (3) USD-denominated budget line (track in USD, convert at month-end) - works for finance teams comfortable with FX volatility.

🎮 Playground

AI Currency Converter Playground

Here are the inputs that move the result the most. Play with the sliders and check it out. The number updates live.

What’s your AI bill in local currency?

Converts your USD spend at your FX rate and shows the swing from currency volatility.

Monthly bill (local)
—

💡Local cost = USD × FX rate. The volatility swing — how much a rate move could add or save — is in “Why this number”.

Three real scenarios

Same calculator, three team sizes. Click a tab to see how the numbers shift.

$50,000 / month ≈ $600,000 / year

Hannah's $50K/mo at 0.92 = €46K. With 8% FX buffer, plan budget €49.7K/mo. Annual €596K vs €552K nominal - €44K buffer for FX surprises.

Healthy range: Plan budget at €50K/mo (vs €46K current) for buffer

See inputs used
monthlyUsdSpend
50,000
fxRate
0.92
fxVolatilityPct
8
targetCurrency
EUR

Use cases

Same calculator, different applications. Sizes above, workloads here. Pick the one that looks like yours.

Pre-loaded scenarios for the most common applications. Click a tab to see realistic numbers, then hit "Try this scenario" to load it into the calculator above.

$25,000 / month ≈ $300,000 / year

Annual budget submission. $25K/mo × 0.78 = £19.5K. Plus 10% FX buffer = £21.5K/mo budget request. £258K annual ask.

Healthy range: Submit budget at +10% of current converted

See inputs used
monthlyUsdSpend
25,000
fxRate
0.78
fxVolatilityPct
10
targetCurrency
GBP

Ready to run the numbers?

Open the full calculator. Pick a model, enter your tokens, see per-call, daily, monthly, and annual cost.

🚀 Open the full calculator →

Top AI vendors (USD baseline)

Verified 13 hours ago
  1. 1
    GPT-5 Mini
    $0.250 in · $2.00 out ·
  2. 2
    gpt-5.1-codex-mini
    $0.250 in · $2.00 out ·
  3. 3
    Command
    $1.00 in · $2.00 out ·

About this calculator: AI Currency Converter - Pricing Across 12 Currencies

AI vendor pricing is USD-denominated. Convert to your local currency for budgeting, finance, and procurement. Live FX rates, current vendor pricing.

🎛 Inputs you control

Each input shapes the cost. Click an input on the calculator to set it. The explanations below match the live calculator field by field.

▸ Input mode: Enter spend as a direct dollar figure, or build it from a model and usage.
How to choose: Pick "Direct dollar amount" if you know your monthly USD bill; pick "From model + usage" to estimate from tokens.
▸ Monthly USD spend: Your known monthly AI spend in US dollars.
How to choose: Enter your actual or projected monthly bill — every currency on the page converts from this.
▸ Model: The model whose published USD pricing is used to estimate spend.
How to choose: Pick the model you actually use; rates are pulled live from the catalog.
▸ Input tokens / request: Average input (prompt) tokens per request.
How to choose: Roughly 750 words is about 1,000 tokens; estimate a typical prompt.
▸ Output tokens / request: Average output (completion) tokens per request.
How to choose: Estimate a typical response; output tokens usually cost more than input.
▸ Requests / day: How many requests you run per day.
How to choose: Use real or projected daily volume; monthly is daily times 30.
📋 Typical values & starting points Don’t know a value yet? Start with these broad, sourced ballparks — the calculator’s ▾ Typical menus pre-load the same options.
Input Default Typical ballparks
monthlyUsdSpend moves the needle 50,000 Pilot spend · ~$500/mo = 500 · Team · ~$5K/mo = 5,000 · Department · ~$50K/mo = 50,000 · Enterprise · ~$250K/mo = 250,000
fxRate moves the needle 0.92 —
fxVolatilityPct 8 —
targetCurrency EUR —

Ballparks are broad industry starting points (sourced ranges; * = rough estimate) — your result gets more accurate as you replace them with measured numbers. Try them live in the calculator; API & agent users get the same data from the MCP resource aicost://input-reference/currency-converter.

Reading your result

Current converted: spend × FX rate. $50K × 0.92 = €46K/mo. €552K annual. Straightforward.

Forward range: ±FX volatility. €46K ± 8% = €42.3K-€49.7K. Annual budget should plan to the upper bound to avoid surprises.

USD spend baseline. Always track AI spend in USD too - vendor invoices, year-over-year comparisons, vendor negotiations all happen in USD. Local currency is for finance reporting only.

What "good" looks like:
  • Stable major currency (EUR, GBP, JPY): 5-10% annual FX swing - plan +10% buffer
  • Emerging markets (INR, BRL, MXN): 10-20% - plan +20% buffer
  • USD-pegged (HKD, AED): <2% - minimal FX adjustment needed
  • Highly volatile (TRY, ARS): 30%+ - consider USD-denominated contract or hedge

What this calculator can't tell you

Honest limitations. Every model is wrong; some are useful. Where this one falls short:

For these, use: Cost Calculator for USD baseline. Annual Forecaster for FX buffer planning.

Trade-offs

Cost isn't the only dimension. Click any constraint to see how recommendations change.

What matters most to you? Click any dimension — recommendations update.

Best fit for "cost":

  1. Annual contract with FX hedge Locks in rate, costs slight premium
  2. USD-denominated budget Eliminates FX from AI cost line

FX exposure on AI is unavoidable for non-USD businesses. Either hedge it (forward contract), absorb it (USD-denominated budget), or buffer it (10-20% extra in local currency budget).

Most popular

Everything above is the 80% case. The last 20% is where the money is.

The gaps we just listed are real, and they are the expensive ones: your actual prompts, your switching cost, your MLOps overhead. An AICost expert spends the hour on your AI and cloud costs, not a generic playbook. You leave with a written report: the way forward, in 30 days of concrete steps.

  • An hour with the people who built the engines
  • Report the same day
  • The fee credits toward any AICost plan
  • Two slots a week
Book a Solution Session: $299 → or $99 for small business →

Not sure yet? The $39 AICost Blueprint credits toward a Session, and the Session fee credits toward any plan. You never pay twice for the same ground. See all pricing →

Ready to run your own numbers?

You have seen the shape of it. Open the calculator with your model, your tokens, your volume.

🚀 Open the full calculator →

Where to go next

12-month forecast with FX buffer →

Layer FX volatility on top of usage growth.

 Single-vendor USD exposure →

Multi-vendor strategy across currency zones.

 Annual contract = FX lock-in →

Pros and cons of locking rate for the year.

Methodology

Source
https://www.ecb.europa.eu/stats/eurofxref/eurofxref-daily.xml
Extraction
FX rates from ECB + central bank reference rates.
Editorial gate
8-layer defense, see aicost.ai/ai-cost-economics
Last verified
7/20/2026, 8:00:00 PM

Author: Subu Vdaygiri, Founder & CEO of CloudIntelligence.ai. 17 years Fortune 100 (Ingram Micro, Siemens). Wharton CTO program · Kellogg CPO program · 10× AWS+Azure certified.

3 years of pricing history

Why this matters: pricing for major vendors has dropped 40-90% in the last 24 months. A budget set 12 months ago is probably wrong by 30%+.

View 3-year history for →
📖 Data sources & methodology 158 text models · 9 embeddings · 37 vision · 55 audio · 8 vector DBs across 10 vendor pages · last verified 2026-07-21

Methodology

  • All prices are USD per 1 million tokens, current as of 2026-07-21.
  • 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
2026-07-21
https://www.anthropic.com/pricing
Daily snapshot since Sep 2023 · 624 days captured
Anthropic Docs
2026-07-21
https://platform.claude.com/docs/en/about-claude/pricing
Daily snapshot since Sep 2023 · 624 days captured
OpenAI
2026-07-21
https://openai.com/api/pricing/
Daily snapshot since Sep 2023 · 625 days captured
Google AI
2026-07-21
https://ai.google.dev/gemini-api/docs/pricing
Daily snapshot since Dec 2023 · 600 days captured
Google Vertex
2026-07-21
https://cloud.google.com/vertex-ai/generative-ai/pricing
Daily snapshot since Dec 2023 · 600 days captured
DeepSeek
2026-07-21
https://api-docs.deepseek.com/quick_start/pricing
Daily snapshot since May 2024 · 539 days captured
xAI
2026-07-21
https://x.ai/api
Daily snapshot since Nov 2024 · 457 days captured
Mistral
2026-07-21
https://mistral.ai/pricing
Daily snapshot since Dec 2023 · 598 days captured
Cohere
2026-07-21
https://cohere.com/pricing
Daily snapshot since Sep 2023 · 624 days captured
Voyage AI
2026-07-21
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.
Google — Gemini 2.0 Flash cachedInput Derived at 25% of input per Google 2.0 family caching rates.
Google — Gemini 2.0 Flash batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 2.0 Flash batchOutput Derived at 50% of output — Google Batch API uniform 50% discount.
Google — Gemini 2.0 Flash-Lite cachedInput Derived at 10% of input — Google caching convention.
Google — Gemini 2.0 Flash-Lite batchInput Derived at 50% of input — Google Batch API uniform 50% discount.
Google — Gemini 2.0 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 →