§ AI Act BRIEFING

GPAI under the AI Act is two tiers: ordinary GPAI under Articles 53–54 and systemic-risk GPAI under Article 55. The threshold between them is one number.

29 GPAI obligations mapped from primary text. The 10²⁵ FLOPS threshold separates documentation duties from systemic-risk audit obligations.

Summary

A general-purpose AI model is, under Article 3(63) of the AI Act, an AI model "trained with a large amount of data using self-supervision at scale, that displays significant generality and is capable of competently performing a wide range of distinct tasks regardless of the way the model is placed on the market." That single definition covers GPT-class, Claude-class, Gemini-class, Mistral-class, Llama-class, Grok-class and Qwen-class models.

Fontvera has mapped 29 obligations across Articles 51–55 to specific actors. The set splits cleanly into two tiers — ordinary GPAI under Articles 53–54, and systemic-risk GPAI under Article 55. The threshold between them is one number: cumulative training compute of 10²⁵ FLOPS, or designation by Commission decision.

Who this applies to
Providers of GPAI models — frontier-lab developers, open-weights publishers, fine-tuners that substantially modify base models, and downstream providers integrating GPAI into AI systems.
Compliance deadline
GPAI obligations (Articles 51 to 56) effective 2 August 2025. Unchanged by the Digital Omnibus provisional agreement of 7 May 2026.
§ Key articles

What the law says

AI Act Article 3(63)
Definition of general-purpose AI model — trained with large amount of data using self-supervision at scale, displays significant generality, performs a wide range of distinct tasks.
AI Act Article 51
Classification — systemic risk if cumulative training compute exceeds 10²⁵ FLOPS, or by Commission decision.
AI Act Article 52
Commission must publish and maintain a list of GPAI models with systemic risk.
AI Act Article 53
All GPAI providers — technical documentation, downstream-information pack, copyright policy, training-data summary.
AI Act Article 53(2)
Open-source carve-out — but only for non-systemic-risk models.
AI Act Article 54
Authorised representative for non-EU GPAI providers.
AI Act Article 55
Systemic-risk GPAI — model evaluation including adversarial testing, systemic risk assessment and mitigation, incident reporting, cybersecurity.
AI Act Article 99(2)
Up to €15,000,000 or 3% worldwide turnover for breach of GPAI obligations.
§ Detail

In depth

The definition — Article 3(63)

An AI model qualifies as GPAI if it satisfies all three conjunctive elements: trained with a large amount of data, self-supervised at scale, displays significant generality with a wide range of distinct tasks. The legal definition is intentionally broad because the regulator wanted to catch frontier-scale models without naming any architecture.

What this excludes: narrow task-specific models (single-task classifiers, specialist forecasting models), small-scale academic models without significant generality, and models distributed exclusively for the personal-research carve-out under Article 2(8).

Tier 1: every GPAI provider — Articles 53 and 54

From Fontvera's obligations corpus (regulation = 'AI Act' AND article_number IN ('53', '54')), the seven Article 53 obligations and ten Article 54 obligations resolve to:

Tier 2: systemic-risk GPAI — Article 55

A model becomes systemic-risk under Article 51 if either:

Six obligations attach in Article 55 — every one in addition to Tier 1:

  1. Model evaluation in line with state-of-the-art protocols, including conducting and documenting adversarial testing to identify and mitigate systemic risks.
  2. Systemic risk assessment and mitigation at Union level — risks stemming from development, placing on the market, or use of the model.
  3. Incident tracking and reporting — track, document and report serious incidents and possible corrective measures to the AI Office and national competent authorities without undue delay.
  4. Cybersecurity — adequate level of cybersecurity protection for the model and the physical infrastructure of the model.
  5. Demonstration of alternative compliance if not adhering to an approved code of practice or harmonised European standard — burden of proof on the provider.
  6. Confidentiality of trade secrets obtained pursuant to the Article in line with Article 78 confidentiality obligations.

Source: Articles 51–55 of Regulation (EU) 2024/1689.

The open-source carve-out — and where it ends

Article 53(2) exempts open-source GPAI providers from the technical documentation duty in Article 53(1)(a) and the downstream-information duty in Article 53(1)(b), provided the model is released under a free and open-source licence with weights and architecture publicly available. The copyright policy at Article 53(1)(c) and the training-data summary at Article 53(1)(d) remain mandatory regardless of licence.

The hard ceiling: Article 53(2) does not apply to systemic-risk GPAI. A 50B-parameter open-weights model trained at frontier scale, once classified systemic-risk under Article 51, owes the full Article 55 obligation set. The licence does not protect against the ten-to-the-twenty-fifth threshold.

Fine-tuning — when does the fine-tuner become a provider?

Recital 109 and Article 25(1) interact here. A fine-tuner that substantially modifies the model — changing its capabilities, intended purpose, or making it suitable for use in high-risk Annex III categories — becomes a new provider for the modified model and inherits the full obligation set. Light fine-tuning for specific downstream tasks does not, in general, trigger new GPAI obligations, but the fine-tuner is still bound by the downstream-information requirements its base provider passed along under Article 53(1)(b).

The boundary is not crisp in primary text. The AI Office is mandated under Article 56 to draw up and approve codes of practice that will articulate practical thresholds — most published draft language treats fine-tuning compute above 1% of base-model compute as material.

Downstream provider duties — what GPAI obligations push to integrators

An AI system provider integrating a GPAI does not automatically inherit Article 53–55 obligations. But:

The AI Act treats GPAI as horizontal; downstream high-risk obligations are vertical. Both can apply to the same model when integrated.

Real numbers Fontvera tracks

Penalty exposure

All Article 53–55 obligations sit in Article 99(2) — Tier 2 — €15,000,000 or 3% of total worldwide annual turnover, whichever is higher. Article 99(7) factor 4 (cooperation and mitigation) is decisive in practice; for systemic-risk GPAI providers, the AI Office can also issue requests for information, conduct evaluations, and require risk mitigation measures under Article 75 — non-cooperation here exposes the provider to Article 99(3) tier 3 penalties (€7.5M / 1.5%) on top.

What good looks like before 2 August 2026

  1. Calculate cumulative training compute with documented methodology. The 10²⁵ FLOPS threshold is the line that determines whether you owe Article 53–54 or also Article 55.
  2. Publish the training-data summary now (the obligation has been live since 2 August 2025). The AI Office template is the format expected; deviation requires alternative-compliance demonstration under Article 53(5).
  3. If open-source, audit the architecture publication — weights public is necessary, architecture description sufficient, and the carve-out evaporates if the model crosses Article 51 systemic-risk classification.
  4. Draft the downstream-information pack for AI system integrators in line with Annex XI Section 2 — failure to deliver here exposes you to Article 99(2) and exposes integrators to their own provider duties without the documentation they need.
  5. Track adversarial-testing protocols for systemic-risk models. The standard expected is the state-of-the-art at the time of evaluation, not the standard at first release.

Run your free AI Act compliance diagnostic

If your team builds, fine-tunes or distributes a GPAI model, the diagnostic returns whether Article 51 systemic-risk applies and which Article 53/54/55 obligations attach.

→ Run the AI Act diagnostic

§ Action items

Practical steps

01
Calculate cumulative training compute with documented methodology — 10²⁵ FLOPS is the line between Tier 1 and Tier 2 GPAI obligations.
02
Publish the training-data summary in the AI Office template format. The obligation has been live since 2 August 2025; deviation requires written alternative-compliance demonstration.
03
Draft the Annex XI Section 2 downstream-information pack for integrators. Without it, you fail Article 53(1)(b) and your customers fail their own provider duties.
04
If open-source, validate the architecture and weights are publicly available — and recompute the systemic-risk threshold each major release.
05
For systemic-risk GPAI, run adversarial testing against the state-of-the-art protocols at evaluation time and document the protocols used.
§ What Fontvera found

Documents in our corpus

eiopa EU Fetched 2026-04
Opinion on Artificial Intelligence governance and risk management
eurlex EU Fetched 2026-04
EUR-Lex: 32025R0454 (2025-03-07)
ai_office EU Fetched 2026-06
§ Cross-references

Related Fontvera intelligence

Need a cross-border briefing on this?
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AI Act Article 50 transparency
50 days
until 2026-08-02, when Article 50 transparency obligations apply (unchanged). Annex III high-risk obligations move provisionally to 2 December 2027 under the Digital Omnibus agreement of 7 May 2026, pending formal adoption.
Preparing for 2 August 2026? Read the EU AI Act August 2026 deadline requirements checklist.