The Open Frontier
We can now see the whole shape of this act. Capable models are given away by labs in several countries, for four different reasons, under licences that range from generous to leashed, and they can run on hardware you own. What does that do to the field?
The barbell
Commoditisation is what happens when a good becomes interchangeable: nobody can charge a premium for it. Every strong open model pushes another capability into the commodity end. The consequence is a barbell. At one end sit closed frontier models, where the best capability is sold per call. At the other sit open models that are good enough and free to host. The middle — a model that is good but not the best, sold as a service — is where the squeeze lands.
The split is measurable, and it moved. On OpenRouter, a large public platform that routes requests to many models, open-weight models overtook closed ones on token volume in mid-2026. Look at spend rather than usage and the gap returns — open weights win a large share of tokens while collecting a small fraction of the revenue. That is the barbell as a number: open weights won usage, and the frontier kept the margin.
Reasoning in the open
The 2025 turn was reasoning. Once DeepSeek showed that reinforcement learning could produce it and released the weights, others followed: reasoning models appeared from Qwen, GLM, Kimi, and more, and small distilled reasoners put a thinking model on hardware that a year earlier ran a plain chatbot. Reasoning went, in months, from a closed frontier feature to an open one — a compression of the usual gap that is itself worth watching.
The question no licence can answer
A guardrail added before release can be removed by anyone who has the weights. Fine-tuning can train safety behaviour away. A model cannot be un-released, and it cannot be patched for everyone at once. This is the sharpest open-weight risk: a public benefit and a public hazard in the same file. Set against it: open weights let more people study a model, and closed systems have their own failure modes — no outside scrutiny, decisions made privately. The honest position is that both ends of the barbell carry risk, of different kinds.
Who gets the value
The barbell answers a question about price. It leaves open the question about people. If a capability someone was paid for becomes a free download, the share of tasks a model can attempt rises fast — an early estimate put a large fraction of US work at high exposure to language models, concentrated in exactly the routine cognitive tasks this guide has spent thirty chapters mechanising. Exposure is not the same as displacement, and the two should never be reported as one. But the distribution of the gains is a real open question: open weights push capability toward anyone, while the margin from the frontier accrues to a handful of labs and their infrastructure. Societal and labour impact is measurable in tasks and largely unmeasured in consequences — which is a reason to watch it, not a reason to skip it.
The closing thought
This act began with a question the first act posed in a different form: what is open? For weights, the answer is now concrete — a file, a licence, a machine that can run it. For the field, it is still contested: whether a model you can run but not rebuild is really open, whether the commodity end makes the frontier safer or the reverse, and whether a capability, once given away, can ever be recalled. Those are the open weights that no one has released yet.