AI pricing, measured
for your workload.
Compare model costs. Track price changes.
The whole idea, in plain English
AI companies charge for the words you send and the words they send back. Images and files count too. Everything is measured in tokens (about ¾ of a word each). Every model prices tokens differently and suits different jobs: a quick model might cost a fraction of a cent, a sharper one fifty times more for the same request.
TokenScale is for the people deciding what to build with AI and what it will cost: curious first-time users, engineers choosing an API, product teams planning a feature, and researchers or leaders checking the market. Start with a familiar task, then compare the trade-offs in plain numbers.
One small job (read 10 pages, write a 1 page summary) costs $0.000160 to $0.0998 depending on the model.
Tiny alone. Run it a million times, a normal day for a live app, and that's $159.60 to $99,750 .
Pick something you'd write
AI companies charge by the word, more or less. Let's see what real writing actually costs.
Technically they charge by the token, a chunk of a word, about three quarters of one. 100 words is roughly 133 tokens. That's the only jargon you need today.
Now pick an AI
Four of the 22 companies TokenScale verifies nightly.
These are raw API prices: the wholesale counter where app developers buy AI by the token. It's not your ChatGPT subscription; that's a flat monthly fee built on top of prices like these.
Your price
Using the current wheel choice: ·
Reading (input) is cheap; writing back (output) costs several times more per token. That's the most misunderstood thing about AI pricing.
Change either answer above and this updates as you go.
Play with AI pricing.Tap the wheel to lock in a model.
or keep exploring below
See how a conversation compounds 10 replies re-read the growing history
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What does this cost at scale? Use the same selected workload at monthly volume
Across all 66 standard-rate model tiers, that same monthly workload ranges from $1.06 to $708.22 . Same volume, different model.
Explore the market DeepInfra leads the cheapest mid-tier list this week
- 1DeepInfra$0.000878—
- 2Cohere$0.00140—
- 3Fireworks AI$0.00140—
- 4Groq$0.00140—
- 5OpenRouter$0.00219—
What does it actually cost to run an AI API call?
It depends on the model and how much text goes in and out. TokenScale shows real examples. Writing the whole of The Hobbit costs about $0.32 on Gemini Flash-Lite 3.5 at list rates as of 9 Sep 2026, and about $0.0051 on the cheapest tracked tier. The same job costs far more on a frontier model. Pick a content size and a provider to see the live figure.
Why does the output price matter more than the input price?
Most providers charge more for the tokens a model generates than for the tokens you send. Output often costs three to five times more than input. A long answer to a short question can cost more than it looks. TokenScale splits every price into input and output so the gap is visible.
How much do AI prices differ between providers?
A lot. Across the 22 providers TokenScale tracks, input rates span roughly 500×, from $0.02 to $10 per million tokens as of 9 Sep 2026, and even models aimed at similar work are routinely more than thirty times apart. Choosing the right provider for a task can cut the bill by an order of magnitude. The comparison table sorts every provider cheapest first.
What is the cheapest way to run a large AI workload?
Pick a low-cost provider and then check that model’s own batch or cached-input terms if your workload can use them. Discounts and eligibility vary by model and provider. TokenScale compares standard on-demand observations, marks carried values, and uses exact model-specific Batch prices where public terms are established; it never applies one universal discount. Open-weight models on inference hosts are often among the cheapest.
Is TokenScale free?
Yes. TokenScale is free, with no sign-up and no account. It runs entirely in your browser. Nothing you type is sent anywhere or stored.
How often is the pricing updated?
Every night. TokenScale checks provider pricing sources and records what the check could reproduce. A successful observation is verified; otherwise the last known value is carried forward and marked for that date.