Computing power
The right size
Why, for most tasks, we use the smallest model that solves them reliably. And how we measure that instead of assuming it.
Does the task need a language model at all?
Sorting texts, for example. A classical method that has been around for decades can do that too.
0.8 secondsversus3 hours 48 minutesThat is how long a 9-watt LED lamp would have to burn to use the same electricity. For the same work, the same batch of texts.
On this scale that is two pixels, and even those are drawn too large.
16,000times more electricity for 0.05 points more accuracy.
Measured for one run over the same test dataset. Source: Comparing energy consumption and accuracy in text classification inference, Scientific Reports, 2026. The lamp time is calculated from it, at 9 watts.
If so, how large does it need to be?
The same model, small and large, the same task.
7times more electricity for 0.07 points more accuracy.
We use the smallest model that solves the task reliably.
Reliably means: it makes no mistakes that go unnoticed. We check that against your own documents before anything goes live.
When we do use a large one
So that this doesn’t sound like penny-pinching: there are tasks where a small model is the wrong choice.
- Free text that looks different every time.
- Images, drawings and photos, especially when they carry dimensions.
- Several languages in one document.
- Wherever a small model would make mistakes that nobody notices.
Then we work with the large providers, and we tell you which one.
What this means for you
Your data
In your systems
The assistant works in the files and programs you use today. Everything else runs in a separate instance of its own on servers in the EU, or on a machine on your premises if you prefer. No training with your data.
The price
Less to run, lower cost
A small model costs a fraction to run. That does not sit in our margin, it sits in your quote.
The consumption
Frugal from the start
Less computing power means less electricity, every day and with every request. That is decided when we build it, not offset afterwards.
Our contribution
The most frugal electricity is the one never used.
Every assistant we build runs on the smallest model that solves its task reliably. That cuts consumption where it arises: in the running of your assistant, every day, with every request. Not afterwards, not somewhere else.
- In the quote
- Which model we use and why it is enough
- In operation
- A separate instance of its own on servers in the EU
- On request
- Estimated consumption per project, to pass on
When your client asks
As a mid-sized company you are not required to report: the threshold is a thousand employees. Your large clients ask anyway.
For every project we provide, on request, one page with the model size, the data centre location and the estimated consumption.
No expert opinion, no advice on reporting duties. Just the figures for the part we run for you, so that you can pass them on.