EU AI Act GPAI Obligations: Gabay sa Kabanata V
Kinokontrol ng Kabanata V ng EU AI Act ang pangkalahatang AI (GPAI) — kung ano ang karaniwang tinatawag na mga batayang modelo. Mayroong dalawang antas: karaniwang mga obligasyon ng GPAI sa ilalim ng Artikulo 53, at karagdagang mga obligasyon para sa mga modelo na may sistematikong panganib sa ilalim ng Artikulo 55.
EU AI Act GPAI Obligations: Gabay sa Kabanata V
Kinokontrol ng Kabanata V ng EU AI Act ang pangkalahatang AI (GPAI) — kung ano ang karaniwang tinatawag na mga batayang modelo. Mayroong dalawang antas: karaniwang mga obligasyon ng GPAI sa ilalim ng Artikulo 53, at karagdagang mga obligasyon para sa mga modelo na may sistematikong panganib sa ilalim ng Artikulo 55.
Huling in-update: Hulyo 4, 2026
Ano ang Itinuturing na GPAI?
Tinutukoy ng EU AI Act ang mga pangkalahatang modelo ng AI sa malawak na paraan:
Isang modelo ng AI na nagpapakita ng makabuluhang pagiging pangkalahatan at may kakayahang magsagawa ng malawak na hanay ng mga natatanging gawain, anuman ang paraan ng paglalagay nito sa merkado. Karamihan sa mga malalaking modelo ng wika, mga modelo ng pagbuo ng imahe, at mga multimodal na batayang modelo ay kwalipikado.
Artikulo 53: Karaniwang mga Obligasyon ng Tagapagbigay ng GPAI
Dapat matugunan ng lahat ng mga tagapagbigay ng GPAI ang mga pangunahing kinakailangan na ito:
- Panatilihin ang teknikal na dokumentasyon kabilang ang proseso ng pagsasanay at pagsubok
- Magbigay ng impormasyon sa mga tagapagbigay na gumagamit ng modelo
- Sumunod sa batas ng copyright ng EU, kabilang ang isang patakaran upang igalang ang mga opsyon sa pag-alis ng pagmimina ng teksto at data
- I-publish ang isang sapat na detalyadong buod ng data ng pagsasanay
- Magtalaga ng isang kinatawan ng EU kung itinatag sa labas ng EU
Artikulo 55: Mga Obligasyon ng GPAI na May Sistemang Panganib
Ang mga modelo na nakakatugon sa limitasyon ng sistematikong panganib (kasalukuyang 10²⁵ FLOPs ng pag-compute ng pagsasanay, bilang indikasyon) ay nahaharap sa karagdagang mga tungkulin:
- Mga pagsusuri ng modelo kabilang ang adversarial na pagsubok
- Pagsusuri at pagpapagaan ng sistematikong panganib
- Mga proteksyon sa cybersecurity
- Pag-uulat ng mga malubhang insidente sa Opisina ng AI
- Pagbubunyag ng pagkonsumo ng enerhiya
Kodigo ng Pagsasanay
Pinadali ng Komisyon ang isang boluntaryong kodigo ng pagsasanay para sa mga tagapagbigay ng GPAI:
Ang pag-aampon ay boluntaryo ngunit nagbibigay ng isang pagpapalagay ng pagsunod para sa mga obligasyon na saklaw nito.
Pagbubukod ng Open-Source
Ang mga open-source na modelo ng GPAI ay tumatanggap ng kanais-nais na pagtrato sa ilalim ng regulasyon:
Ang mga modelo ng GPAI na inilabas sa ilalim ng mga libre at open-source na lisensya ay halos exempted mula sa Artikulo 53, maliban sa mga obligasyon sa copyright at buod ng data ng pagsasanay — at ang pagbubukod ay hindi nalalapat sa mga modelo na may sistematikong panganib.
GPAI Compliance Timeline
The Chapter V obligations phase in on their own schedule, distinct from the high-risk deadlines:
- 2 August 2025 — the GPAI provider obligations under Articles 53 and 55 begin to apply to models placed on the market from this date
- 2 August 2026 — the AI Office's supervisory and enforcement powers over GPAI providers become applicable
- 2 August 2027 — GPAI models already on the market before 2 August 2025 must be brought into compliance by this date
- Signing the Code of Practice — providers who adhere to the GPAI Code of Practice can rely on it to demonstrate conformity while harmonised standards are still being developed
Dates reflect Regulation (EU) 2024/1689 as it stands; confirm against the latest Official Journal text and AI Office guidance, which may evolve.
How AIAgentree helps
AIAgentree governs how your agents use GPAI models in production, giving you the downstream documentation and incident evidence Chapter V expects.
- Tamper-evident decision records log how a GPAI-backed agent reasoned toward each decision, giving you durable evidence for downstream-provider documentation and serious-incident reporting
- Human-oversight and approval workflows plus outcome tracking help you evidence the risk-mitigation and monitoring practices Article 55 asks of systemic-risk deployments
- Python and TypeScript SDKs with REST, MCP, A2A, and OpenTelemetry integrate model-usage evidence into your compliance stack, with EU data residency in Germany and audit-fit retention of at least six months
Frequently Asked Questions
What counts as a general-purpose AI model under the EU AI Act?
A GPAI model is one that displays significant generality and can competently perform a wide range of distinct tasks, regardless of how it is released. Most large language models, image-generation models, and multimodal foundation models fall within this definition.
What is the systemic-risk threshold for GPAI?
A GPAI model is presumed to carry systemic risk when the cumulative compute used for its training exceeds 10^25 floating-point operations, an indicative threshold the Commission can adjust. Such models face extra duties under Article 55, including model evaluations, adversarial testing, risk mitigation, cybersecurity, and serious-incident reporting.
Is the GPAI Code of Practice mandatory?
No. The Code of Practice is voluntary. Providers who adhere to it can use it to demonstrate conformity with their Chapter V obligations while harmonised standards are still being finalised; providers who do not sign it must demonstrate compliance by other adequate means.
Are open-source models exempt from the GPAI rules?
Only partly. GPAI models released under a free and open-source license are largely exempt from the Article 53 obligations, but they must still meet the copyright-policy and training-data-summary duties. The exemption does not apply at all to models that meet the systemic-risk threshold.
Continue exploring the EU AI Act guide
EU AI Act Compliance Guide
The complete guide to EU AI Act compliance for AI agents — start here.
Article 12 — Record-Keeping & Logging
What every high-risk AI system must log, and how to capture it.
Article 14 — Human Oversight
Designing effective human-in-the-loop controls for AI decisions.
Annex III — High-Risk AI Systems
Which AI use cases the Act classifies as high-risk.
EU AI Act Compliance Checklist
A step-by-step checklist to reach and document compliance.
Compliance Cost Calculator
Estimate your EU AI Act compliance effort and cost.
Deadlines & Timeline
Key enforcement dates, including the August 2, 2026 deadline.
Fines & Penalties
Penalty tiers up to €35M or 7% of global annual turnover.
Transparency Obligations (Art. 13 & 50)
Disclosure duties for AI systems and their outputs.
Risk Management & Conformity Assessment
Build a risk management system and assess conformity.
EU AI Act for US Companies
Extraterritorial scope and what US providers must do.
Omnibus Update
The latest changes to the EU AI Act timeline and rules.
Penalty Calculator
Estimate your maximum fine under the Article 99 tiers.
Article 11 + Annex IV
What technical documentation the EU AI Act requires.
Article 26: Deployer Obligations
What deployers of high-risk AI must do, including log retention.
Article 17: Quality Management
The QMS providers of high-risk AI must document.
Article 10: Data Governance
Data quality, bias mitigation, and governance duties.
Article 4: AI Literacy
The staff AI-literacy duty in force since February 2025.
Deployer vs Provider
Who bears which obligation — and when a deployer becomes a provider.
FRIA (Article 27)
Who must run a Fundamental Rights Impact Assessment, and how.
Who Does It Apply To?
Scope, operators, and the extraterritorial reach of the EU AI Act.
Post-Market Monitoring
Articles 72–73: ongoing monitoring and incident reporting.
ISO 42001 vs EU AI Act
How the voluntary standard and the binding law fit together.
NIST AI RMF vs EU AI Act
A practical crosswalk between the framework and the law.
EU AI Act for Healthcare
High-risk medical AI, MDR/IVDR interplay, and clinician oversight.
EU AI Act for Financial Services
Credit scoring, insurance pricing, and existing financial regulation.
EU AI Act for HR & Employment
Hiring AI as high-risk, plus NYC LL144 and EEOC overlap.