Why there is no token bill

Rented AI has a strange habit. The price of a token keeps falling, and the bills keep rising. Bain put numbers on it in September 2026: the price per token fell to 0.42 times what it was, and the bill more than doubled, because use grew faster than the price fell.1

For a company that uses AI lightly, that is fine. For a company that puts AI into its core work, it means the bill grows with every success. The more your people rely on it, the more you pay, and the model is still not yours.

AI-first startups feel it first. Their API bill grows with every customer, often faster than their revenue, and the model their product runs on belongs to someone else. That is why we started Eigna Ventures: we run the startup’s own model and its infrastructure as a partner.

A fixed cost instead of a meter

An Eigna model runs on a machine: your servers, an Eigna Box on your site, or a dedicated GPU in the region you choose. A machine costs a fixed amount each month, not an amount per answer. So we price the way the cost works: once to set the model up, then a fixed running fee to run it and keep it learning.

There is no seat count and no meter. The more a team uses its model, the cheaper each answer gets.

Where the flat fee wins, honestly

A fixed fee is not cheaper for everyone, and we will not pretend it is. We worked out where one Eigna Local site at $1,100 a month breaks even against rented models at list prices, with three input tokens for every output token:2

• About 98 million tokens a month against GPT-5.5.
• About 275 million tokens a month against Claude Sonnet 5.5.
• About 5.5 billion tokens a month against Claude Haiku 5.5.

That is real for heavy, steady use of the mid and top tiers. Against the cheapest tier we make no cost claim at all. If your use is light, rent. Keep a rented assistant for email and office work, where it is the right tool.

Cost is not the whole case

Below the break-even point, the case for owning is not price. It is quality on your task, a model that stays the same until you decide, and data that stays where the run mode says. With Eigna Local: data never leaves. With Hybrid and Cloud: data stays in the region you choose.

Our own cost keeps falling, too. Open models get smaller and better each year, so serving a model gets cheaper for us while the model you own is worth more to you. That is the bet under the price: a cost you can plan, on a model that compounds on your side of the table.

What we still have to show

These prices stay proposals until the first clients pay for a Test Lab. Throughput per Eigna Box tier and per GPU is still to be measured, so we publish no cost per answer yet. When we have it, it will be here, next to its baseline.