Prometheus Plan

FR

Prometheus Plan

France can win the AI race. What would it cost?

Tristan Claret-Trentelivres, Raphaël Doan, Aymeric Roucher and Victor Storchan

June 2026

Originally published in Le Grand Continent

Contents

The only question that matters

Creating a frontier lab for France

What is a frontier lab?

Compute, the sinews of war

What would such a project cost?

Compute

Recruitment

Total

Bootstrap, self-sustaining trajectory and financial returns

How to carry this plan through?

Vehicle

What coalition around France?

The first three years

International opposition

Strategic alternatives

The other paths are just as risky

Why act now

Our conclusions

01<br>The only question that matters

The American administration recently imposed export controls on Anthropic's most advanced large language models, Mythos and Fable 5. The decision to restore access, taken on 30 June 2026, marks the entry into a new regime: no administration will want to lock itself into rigid transparency criteria for granting the best artificial intelligence models access to the market. A kind of strategic ambiguity will be the rule. The American government will seek to preserve maximum room for manoeuvre, including the ability to withdraw access to a model without notice and at its discretion, or to restrict its use cases.

That decision reminded everyone of the urgency of the situation: artificial intelligence is becoming a resource as important as electricity or oil in our economy. Securing its supply is now a decisive strategic question. In an economy now durably irrigated by large language models (LLMs), not having autonomous access to the best models, those we call frontier models, means depending on others for a growing share of our productivity, our industrial power and our national security. If certain model capabilities cross a threshold (autonomy on long tasks, greater reliability, falling inference costs), adoption could break sharply upward, potentially triggering a rapid economic decoupling of the countries that lack them. In fact, no economic question, and probably no strategic one, matters more today than this: will we be subject to the goodwill of foreign powers to supply our society with machine intelligence, or will we be able to produce it ourselves?

In artificial intelligence, France certainly has many advantages, starting with its nuclear fleet and the excellence of its researchers and engineers. It hosts the only European lab able to produce large language models of reasonable size, Mistral. But that is still a long way from having a lab able to supply first-rank artificial intelligence, and to follow or even lead the advances of the frontier. In that respect, we are in fact starting almost from zero.

If France and Europe have failed to produce champions as powerful as Anthropic or OpenAI, it is for structural reasons tied to the dispersion of capital, the regulatory environment, and probably to cultural behaviours. It is hard to imagine changing these parameters quickly: the unification of European capital markets is a perennial mirage, and so is the simplification of national and European law. One can safely say that a cutting-edge artificial intelligence lab will not develop there organically. Any political will to put France back into the artificial intelligence race can therefore only work through a deliberate effort by the state.

But what effort are we talking about, and on what scale? Most of those who call today for sovereign artificial intelligence do so without measuring its price. Yet the political equation changes entirely with the order of magnitude. Is it equivalent to the cost of a new aircraft carrier, for example? Is it rather an effort comparable to the Messmer plan, which for a time mobilised more than 1% of French GDP to build the fleet of nuclear reactors that is still our energy backbone? Does it go further still?

In this note we propose a “Prometheus Plan”: we compute the amounts to invest to create and sustain a frontier lab in France within three years, before determining by what means to get there and drawing the strategic conclusions that follow.

02<br>Creating a frontier lab for France

We deliberately reason about a lab dedicated to large language models, because it is today the most mature, and therefore the most reproducible, general-purpose artificial intelligence technology. Betting on still unproven paradigms, such as world models, remains useful and desirable, but as a complement to an industrial project of this kind, just as it was necessary in the 1970s to copy and deploy in France the American light-water reactor design, independently of French research on alternative reactor designs.

What is a frontier lab?

The term “frontier”, in AI, describes a dynamic unfolding over time more than the performance of a model at a given moment: the duration, measured in expert human time, of the tasks an agent can complete with a given level of reliability has...