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Side by side

Claude vs GPT: what the same workload costs on each

One set of inputs, two bills. Enter the calls you make a month and the tokens per call once, and the page prices them on Claude and on GPT together so the difference is a number rather than an opinion.

Nothing here is gated. No signup, no email, no credentials.

Your usage

Change anything here and every number on the right updates straight away.

Rates come from the same published price table Cost uses to price the calls it meters.

The same calls and the same tokens, priced on a second model.

Start from a typical workload

These load ordinary figures for each shape of work. Change any of them below; the sum follows.

Every request your app makes to the model API, across all routes.

System prompt, retrieved context and the user message. Roughly 750 words is 1,000 tokens.

What the model writes back. Output usually costs about five times as much as input.

25%

The share of your input tokens served from the prompt cache. If the model has no published cached rate, this changes nothing and the working says so.

Estimated model spend

€1,470per month

Exact, in euro
€1,469.70
In dollars
$1,597.50
Per call
$0.010650
Per year
€17,636

The working

Every step, in order. If we quoted you a figure by email, this is how we got it.

  1. 1Model: claude-sonnet-5 on Anthropic.
  2. 2Published rate: $2.00 per 1M input tokens, $10.00 per 1M output tokens, $0.20 per 1M cached input tokens.
  3. 3Usage: 150,000 calls a month, 3,000 input tokens and 600 output tokens per call.
  4. 4Cache: 25% of the input is a cache hit, so 750 tokens are billed at the cached rate and 2,250 at the full input rate.
  5. 5Input per call: 2,250 / 1,000,000 x $2.00 = $0.004500
  6. 6Cached input per call: 750 / 1,000,000 x $0.20 = $0.000150
  7. 7Output per call: 600 / 1,000,000 x $10.00 = $0.006000
  8. 8Cost per call: $0.010650
  9. 9Cost per month: 150,000 x $0.010650 = $1,597.50
  10. 10In euro at 0.92 USD to EUR: $1,597.50 x 0.92 = €1,469.70
  11. 11This counts API token cost only. It does not include cache-write charges, retries, embeddings, batch discounts or anything you spend outside the model API.

Converted at a standing rate of 0.92 USD to EUR. The dashboard uses the live daily rate instead, so your real invoice will differ by a percent or two.

What that model would cost instead

claude-sonnet-5
€1,469.70
gpt-4o
€1,733.63

€263.92a month more

€3,167 a year

The working, compared

The same arithmetic on the second model, and the difference.

  1. 1Compared with: gpt-4o on OpenAI, at exactly the same usage.
  2. 2Published rate: $2.50 per 1M input tokens, $10.00 per 1M output tokens, $1.25 per 1M cached input tokens.
  3. 3Cost per call on gpt-4o: $0.012563
  4. 4Cost per month: 150,000 x $0.012563 = $1,884.38, which is €1,733.63.
  5. 5Difference: €1,733.63 - €1,469.70 = €263.92 a month dearer on gpt-4o.
  6. 6Over twelve months: €263.92 x 12 = €3,167.10.
  7. 7Same tokens and the same cache hit rate on both sides. A cheaper model may need longer prompts or more retries, and this does not model output quality.
Show the full sum for gpt-4o
  1. 1Model: gpt-4o on OpenAI.
  2. 2Published rate: $2.50 per 1M input tokens, $10.00 per 1M output tokens, $1.25 per 1M cached input tokens.
  3. 3Usage: 150,000 calls a month, 3,000 input tokens and 600 output tokens per call.
  4. 4Cache: 25% of the input is a cache hit, so 750 tokens are billed at the cached rate and 2,250 at the full input rate.
  5. 5Input per call: 2,250 / 1,000,000 x $2.50 = $0.005625
  6. 6Cached input per call: 750 / 1,000,000 x $1.25 = $0.000937
  7. 7Output per call: 600 / 1,000,000 x $10.00 = $0.006000
  8. 8Cost per call: $0.012563
  9. 9Cost per month: 150,000 x $0.012563 = $1,884.38
  10. 10In euro at 0.92 USD to EUR: $1,884.38 x 0.92 = €1,733.63
  11. 11This counts API token cost only. It does not include cache-write charges, retries, embeddings, batch discounts or anything you spend outside the model API.

This model has an announced price rise

From 2026-09-01, the same usage costs €2,205 a month, which is €734.85 more than today.

  • Introductory pricing ends 2026-08-31. Input and output both rise 50%.
  • New rate from 2026-09-01: $3.00 per 1M input tokens (was $2.00), $15.00 per 1M output tokens (was $10.00).
  • Same usage at the new rate: $2,396.25 a month, which is €2,204.55.
  • That is €734.85 a month more than today, an increase of 50%.

Source: anthropic.com, checked 2026-08-01. If that page now says something else, believe it over this one.

Want the full breakdown by route?

We can send you a written report that takes this estimate apart: which model tiers you could drop to, what prompt caching would actually save you, and where the same spend usually hides in a codebase like yours. Leaving an email is entirely optional. The calculator above is complete without it and nothing on this page is hidden behind a form.

We store your address and the figures above so we can write the report. Nothing else, and no third-party trackers. See the privacy page.

How this actually gets billed

A price comparison between two models is only half the question. The other half is whether the cheaper one is good enough on your traffic, and no pricing page can answer that. Cost shadow-runs the cheaper model against real requests and has an independent judge score the answers before anything is switched.

Compare like for like. The headline rate per million tokens is not comparable across providers until you have accounted for how each one bills cached input, and for how verbose each model is on your prompts. A model with a lower rate that answers at twice the length is not cheaper.

The cheapest migration is usually not a migration. Most teams who price this comparison discover the win is moving some routes down a tier inside the provider they already use, rather than moving providers at all.

If you would rather not guess at token counts, upload a usage export on the free analysis page and we will work from your real numbers. Or wrap one client with the SDK and see it measured, on the free tier.

Questions people ask

Which is cheaper, Claude or GPT?
It depends entirely on the model pair and your output lengths, which is why this page makes you enter your own numbers rather than publishing a verdict. Put your figures in and the two totals appear side by side.
Does switching provider actually save money in practice?
Sometimes, and less often than the rate cards suggest. Output verbosity, retries and prompt rewriting eat into the gap. The way to know is to run the cheaper model against your own traffic and score the answers before you commit.

Price something else