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AMÁLIA — Portugal's Open-Source Large Language Model for European Portuguese

Portugal · Lisbon · See the Portugal profile

A five-university consortium built AMÁLIA, Portugal's first open-source LLM for European Portuguese, for about €7m in PRR funds, launched 1 July 2026 at 9 billion parameters. It is in limited beta with four pilot users; independent press calls it "not yet fully operational".

9 billion parameters
Model parameters (at launch)
7 million EUR
Project cost through 2027 (through 2027)
4 pilot users
Validated pilot users at launch (at launch (1 July 2026))
60+ researchers
Researchers involved in development (development)
32,000 tokens
Context window (at launch)
22 billion parameters
Planned future model size (roadmap by 2027)
AMÁLIA — Portugal's Open-Source Large Language Model for European Portuguese

Details

Maturity
Pilot
Promoter
Ministério da Reforma do Estado / Agência para a Reforma Tecnológica do Estado (ARTE), with a consortium led by NOVA University Lisbon, Instituto Superior Técnico, and the universities of Coimbra, Porto and Minho
Period
Base version delivered September 2025; publicly unveiled 1 July 2026, roadmap to 2027
Keywords
sovereign large language model, open-source AI, digital sovereignty, public-sector AI infrastructure

Context

Portugal sought sovereign AI infrastructure for European Portuguese amid a broader European debate on AI sovereignty.

Objectives

AMÁLIA is Portugal's first large language model built specifically for European Portuguese, intended as open-source public digital-sovereignty infrastructure.

Activities

Developed by a five-university consortium — coordinated by NOVA University Lisbon with Instituto Superior Técnico and the universities of Coimbra, Porto and Minho, involving more than 60 researchers — the model extends the open, European-funded EuroLLM-9B foundation model to 9 billion parameters, plus separate vision and speech-recognition components and a 32,000-token context window. It was released open-source under an Apache 2.0 licence on Hugging Face, funded through Portugal's Recovery and Resilience Plan (PRR).

Results

Publicly unveiled 1 July 2026, AMÁLIA has no public chat interface and experimental search capability only; it is running in a limited beta with four validated pilot users (museum, science, media and education bodies) for tasks such as answering visitor questions about artworks. The project cost around EUR 7 million through 2027, with a roadmap toward a 22-billion-parameter version by 2027.

Conclusions

Independent Portuguese and international press explicitly caution that the model 'is not yet fully operational,' that it is an adaptation of an existing multilingual model rather than an original build, and that at 9 billion parameters it is far smaller than leading commercial systems — an honest, evidence-thin starting point rather than a finished public-sector deployment.

Implementation

Indicative cost
High (€500k–€5M) — Approximately EUR 7 million total through 2027 (an initial EUR 5.5m plus EUR 1.5m more), funded through Portugal's Recovery and Resilience Plan (PRR).
Time to results
Medium (1–3 years) — Base version delivered September 2025; publicly unveiled 1 July 2026; roadmap to a 22-billion-parameter version by 2027.
Staffing & skills
five-university consortium (NOVA University Lisbon coordinating; Instituto Superior Técnico; universities of Coimbra, Porto, Minho), 60+ researchers, Ministry for State Reform / ARTE (State Technological Reform Agency), Foundation for Science and Technology (FCT) — funding body

Conditions for success

  • building on an existing open European foundation model (EuroLLM-9B) rather than training from scratch
  • open-source Apache 2.0 release enabling public bodies, companies and universities to build on it directly
  • a multi-university research consortium pooling expertise
  • public PRR funding with a defined roadmap to a larger 22B-parameter version

Common failure modes

  • no public chat interface at launch; search capability experimental only
  • only four validated pilot users so far
  • independent press caution that it is an adaptation of an existing model, not an original build, and far smaller than leading commercial systems

Where it fits

Governance type
national ministry, state agency and university consortium
Scale
national, early pilot (4 users)
Income level
high-income

Data sources

Where this practice's information was retrieved from, and when.

Attachments

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