MTok pricing is the industry-standard billing unit for LLM APIs: dollars per million tokens, quoted separately for input (your prompt and context) and output (the model's response). In our LLM API price index, list rates run from $0.05 in / $0.40 out (GPT-5 nano) to $30 in / $180 out (GPT-5.5 Pro), each read from the provider’s own pricing page. The headline pair is only part of the card: cached input, cache writes, long-context tiers and batch discounts change what you pay.
Why it matters
Every provider quotes it, and almost nobody can translate it into a bill, because bills depend on token counts that vary by model and task. Two models with identical rate cards can produce meaningfully different bills on the same prompt.
How to read a rate card
Three of these four models share the same headline price, $2 in and $10 out per million tokens. The lines under the headline are where they differ. Rates from each provider’s pricing page, in US dollars per million tokens, checked October 27, 2026.
| Model | Input | Cached input | Output | What else is on the card |
|---|---|---|---|---|
| Claude Sonnet 5 | $2.00 | $0.20 | $10.00 | Cache writes $2.50 (5-minute) or $4.00 (1-hour); 50% batch discount |
| GPT-6.1 Sol | $2.00 | $0.10 | $10.00 | Above 272K input tokens: $4.00 in / $15.00 out; 50% batch discount |
| Gemini 4 Argon | $2.00 | $0.10 | $10.00 | Scheduled to rise to $4.00 in / $20.00 out on December 1, 2026 |
| Pareto 26.10 | $0.80 | $0.03 | $3.20 | Pay-as-you-go API rate; subscriptions are priced per month |
Sources: Anthropic pricing, OpenAI pricing, Gemini API pricing, Unbiased pricing. Every row and its history: the LLM API price index.
Turning per-MTok rates into a bill
Divide each token count by one million, multiply by its rate, and add the lines: input tokens × input rate + cached tokens × cached rate + output tokens × output rate, all over 1,000,000.
Worked example on Claude Sonnet 5: a 10,000-token prompt where 8,000 tokens are a cached system prompt, plus a 1,000-token answer. Fresh input is 2,000 × $2.00 = $0.0040, cached reads are 8,000 × $0.20 = $0.0016 and output is 1,000 × $10.00 = $0.0100, each divided by a million. That is $0.0156 per request. With no cache the same request is $0.0200 + $0.0100 = $0.0300. The first request that writes the cache pays the write rate ($2.50 per MTok for the 5-minute cache) on those 8,000 tokens instead of the cached rate.
What moves the number
- Cached input. Of the 59 models in the index with a cached-input price, 34 bill cache hits at one tenth of the input rate. See prompt caching and the caching cost calculator.
- Cache writes. Anthropic charges extra to write the cache: on Sonnet 5, $2.50 for a 5-minute cache and $4.00 for a 1-hour cache, against $2.00 for plain input.
- Long-context tiers. Some cards switch to a higher rate once the prompt passes a threshold: 272K input tokens on OpenAI’s GPT-6, GPT-6.1 and GPT-5.4/5.5 rows, 200K on Gemini 2.5 Pro and Gemini 3.1 Pro Preview, and 200K or more on xAI’s Grok rows.
- Batch. 33 of the 60 models list a 50% discount for asynchronous batch jobs. See Batch API.
- Time of day and scheduled changes. DeepSeek lists lower off-peak rates, and some providers publish dated rises in advance, like Gemini 4 Argon on December 1, 2026. Dated moves are collected in the AI price tracker.
Measured: same rates, different bills
We sent one identical prompt to Claude Opus 5 and Opus 4.8, which share a $5/$25 rate card. Opus 5 wrote 4,610 output tokens; 4.8 wrote 2,877. The bills: $0.1158 versus $0.0724, 60% apart at identical prices, because verbosity is billed. Rate cards start the estimate; metered bills finish it. Full ladder with measured task costs in the pricing guide.
Common questions
How many tokens is a page of text?
Roughly 500-600 tokens for a dense page of English prose, at about four characters per token. Code runs denser, around 3.5 characters per token.
Why is output priced higher than input?
Output tokens are generated one at a time and cost more compute than reading the prompt. Five times the input rate is the most common ratio: 27 of the 60 models in our price index price output at exactly 5x input, and the range runs from 2x (Grok 4.20 Multi-Agent) to about 8.3x (Gemini 3.5 Flash-Lite).
What is a normal monthly spend?
Wildly workload-dependent: our calculator prices 1,000 daily code-generation requests at anywhere from $408/month (Haiku 4.5) to $4,080/month (Fable 5) at list rates.
Does cached input count toward MTok pricing?
Yes, at its own rate. Cache hits are billed per million tokens like any other input, usually at a fraction of the input price: one tenth on 34 of the 59 models in our index that list a cached rate. Some providers also charge a separate, higher rate to write the cache.
Compare any two models
List rates and dated competitor measurements: prices and measured bills. Preliminary Pareto 26.10 benchmark costs per task from October 1, 2026 are on the model card. Verbosity: Edition 2.
Try it on one part of your codebase
Set Pareto up in the coding agent you already use and give it a week of real work. Pareto starts at $10 a month.
Read https://unbiased.ai/glossary/mtok-pricing/ and tell me what matters for my setup. If Pareto fits, read https://unbiased.ai/works-with/agent.md, find the coding agent I use on this machine, and set it up to use Pareto. Ask before changing any file, and never ask me to paste my API key into chat.
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