Three things the field repeats about serving open models do not survive when rubber meets the road. Here are the numbers, and here is my Vendor neutral, no Agenda, opensource calculator & a Paper https://tokencalci.onrender.com/

Open weights are free. Serving tokens is not.
Self-hosting can be cheaper if utilization is high, Structural request and many other options.

A weight file is an artefact. A served token is a complex system. Between them sit ten cost-bearing layers of work, and exactly one of them arrives in the download.

We have seen this shape before. Around 2008–09 we had App source code and increasingly realized that shipping software to millions required a discipline beyond writing it. We eventually named that discipline live DevOps, SRE. Only after it had a name, did organisations budget for it, hire for it, put it on a chart. Model serving sits at the same point now. Everyone doing the work knows it. Almost nobody buying(Token via API) it does.

An unnamed cost is not a cheap cost. It arrives late, in a different quarter, attributed to something else.

"More GPUs, more throughput." Eight GPUs serve roughly what one does. Splitting a model across devices makes it fit. It does not make it fast. An earlier version of my own tool got this wrong and oversized fleets by 2.4×.

"Self-hosting loses on hardware." Bare compute runs Llama 3.3 70B at $0.037 per million tokens. A neocloud charges $0.252 for the same weights. You do not lose on silicon. You lose on idle capacity, which is 185% of the gap, and on the people to run the stack, which is 42%.

Tokencalci A vendor neutral Calculator starts from your workload, not a hardware wish list. Requests a day, input and output sizes, traffic shape, concurrency, serving precision. It returns the fleet you need, the utilisation you will reach, and your cost per million tokens against a live median of 14 provider listings. We run it for a 1,000-person organisation, then move the assumptions and watch the break-even move.

One number to hold before you arrive: the same open weights list from $0.10 to $1.04 per million input tokens across 14 providers. Which provider you sign with moves the answer more than any engineering decision on the page.

Having described the 10 layers in my paper.
Nine of the ten layers are engineering. You hire them, buy them, or take them from open source. Layer nine is different. A provider pools demand across thousands of customers whose peaks do not coincide. You pool across one customer, yourself, and your applications peak together because they serve the same business on the same working day. Utilisation is structural, not a skill problem.

The paper marks every claim as measured or reasoned, states its limits in a numbered section. Tool and paper are both open and free.

You leave with the calculator, the ten layers, and one question for your own organization. Do you have the equivalent of an SRE discipline for serving tokens?