📊 Full opportunity report: ALIA. The Spanish answer. on ThorstenMeyerAI.com — validation score, market gap, and execution plan.
TL;DR
Spain has launched ALIA-40B, a 40-billion-parameter multilingual AI model, funded entirely by public money. The project aims to boost Spanish and European AI capabilities, but benchmark results reveal operational limitations compared to Llama 2.
Spain has officially released ALIA-40B, a 40-billion-parameter multilingual AI model trained on more than 9.37 trillion tokens, making it Europe’s largest publicly funded AI project to date. The model, developed by the Barcelona Supercomputing Center and funded with over €240 million from public sources, aims to serve as Spain’s institutional answer to European sovereignty in artificial intelligence and to promote widespread adoption of AI in the Spanish-speaking world.
ALIA-40B was trained on 35 European languages and 92 programming languages, and is available under the Apache License 2.0 on HuggingFace since April 22, 2025. It was developed using MareNostrum 5’s 4,480 NVIDIA H100 GPU accelerated infrastructure, with funding allocated specifically for upgrades and integration into industry sectors. The project is led by the Secretary of State for Digitalisation and Artificial Intelligence (SEDIA), with technical coordination by the Barcelona Supercomputing Center.
Benchmark results indicate that ALIA-40B performs below Llama 2 on key NLP tasks—achieving 51.77% accuracy on XNLI in English versus Llama 2’s 66%, and 81.53% on SQuAD in English compared to Llama 2’s 93-94%. Despite these results, project leaders emphasize that ALIA’s strategic focus is on widespread adoption within the Spanish-speaking world, rather than achieving top benchmark performance. The model’s multilingual scope and open-source licensing are intended to foster regional integration and transparency.
ALIA.
The Spanish
answer.
€240M+ Spanish public funding · ALIA-40B + Salamandra family · 9.37T tokens · 35 European languages + 92 programming languages · MareNostrum 5 · Apache 2.0 release. The largest publicly funded European national-AI project by cumulative scope — and the empirical test case for the Position 1 vs Position 3 strategic-positioning argument.
This is the tenth standalone essay in the European sovereign-LLM track and the third Tier 2 expansion piece. ALIA is Spain’s institutional answer — the largest EU member state by GDP not yet documented in the track. The project markets itself as Position 1 + Position 2 simultaneously — “Europe’s first public multilingual foundational model.” The benchmark evidence (ALIA-40B 51.77% XNLI_en vs Llama 2 66%) confirms the structural capability gap from Finding 1 of the synthesis essay. The Position 3 framing — Martorell’s “most widely adopted in the Spanish-speaking world” — is operationally honest. €90M MareNostrum 5 upgrade + €150M company integration = €240M+ cumulative scope. Apache 2.0 open-source release + AESIA validation + co-official languages oversampling. Both can be true at once. The Spanish public discourse would benefit from explicit Position 3 strategic positioning.
Six models. Apache 2.0.
The ALIA family operates as a tiered model portfolio. ALIA-40B is the flagship at 40 billion parameters; the Salamandra family scales down to 7B, 2B and instruct-tuned variants; mRoBERTa provides the foundational multilingual baseline. All released under Apache License 2.0 on April 22, 2025 at the HispanIA 2040 event — “Public Code, Public Money” approach.
multilingual
MN5 LLM
edge
target
instruct
encoder
multilingual AI language model
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Four official. Oversampled by factor of 2.
ALIA’s distinctive multilingual coverage strategy. The four co-official Spanish languages are oversampled by factor of 2 in the training corpus — structurally distinct from Apertus’s broad 1,811-language coverage approach. The strategy targets deep coverage of Spanish co-official languages rather than maximum language breadth.
open source NLP models
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ALIA-40B vs Llama 2. 14-point gap.
The empirical evidence Finding 1 of the synthesis essay needed. ALIA-40B at 40 billion parameters with €240M+ public funding and 8+ months MareNostrum 5 training achieves performance below Llama 2 — a 2023 frontier model released approximately 18 months before ALIA-40B. The capability gap is real and consistent with six of seven prior national-project answers documented in the track.
AI Systems Performance Engineering: Optimizing Model Training and Inference Workloads with GPUs, CUDA, and PyTorch
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Two pilots. Public administration deployment.
The operational deployment targets that validate the Position 3 + Position 4 framing. Public administration deployment is the structurally credible Position 3 + Position 4 strategic positioning — captive demand from Spanish public institutions where Spanish-language specialization is operationally distinctive.
The work is real across the Spanish ALIA case. €240M+ public funding committed. 40B parameter from-scratch model trained on 9.37 trillion tokens. Salamandra family released under Apache 2.0. AESIA validation aligned with EU AI Act transparency standards. Two pilot applications shipped — Tax Agency chatbot and primary care medicine heart failure diagnosis. The Position 1 framing is operationally misleading. ALIA-40B performance below Llama 2 confirms the structural capability gap. The Position 3 framing is operationally honest — Spanish-speaking world adoption, co-official languages oversampling, public administration deployment. Both can be true at once. The Spanish public discourse would benefit from explicit Position 3 strategic positioning.
European AI development tools
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Implications of ALIA’s Strategic Positioning and Performance
ALIA’s launch underscores Spain’s commitment to establishing a sovereign AI infrastructure that prioritizes regional language coverage and openness over top-tier benchmark performance. While benchmark results reveal a capability gap compared to Llama 2, the project exemplifies a strategic choice to focus on operational relevance within the Spanish-speaking world. This approach aligns with Spain’s broader goal of fostering AI adoption across government, industry, and academia, and sets a precedent for other European nations pursuing similar sovereignty strategies.
Moreover, the substantial public investment of €240 million highlights the importance placed on AI as a national strategic asset. The emphasis on multilingual, open-source models also raises questions about Europe’s competitive positioning in global AI development, especially given the performance limitations observed thus far.
Spain’s Public AI Investment and European Sovereignty Efforts
Spain’s ALIA project is part of a broader European initiative to develop sovereign AI capabilities, supported by substantial public funding and infrastructure upgrades. It follows earlier national projects like Portugal’s AMÁLIA and Italy’s Minerva, but surpasses them in scale and scope. The project is coordinated through the Barcelona Supercomputing Center and is aligned with Spain’s 2024 AI strategy, which allocates €150 million specifically for ALIA’s integration into industry and government applications.
Developed amidst a landscape of European efforts to reduce reliance on US and Chinese AI models, ALIA represents a strategic move to create a domestically controlled, multilingual AI infrastructure. The project also aims to demonstrate transparency and operational honesty, contrasting with other models that often emphasize benchmark performance over regional relevance.
“The goal is not to be the best-performing LLM in the world, but the most widely adopted in the Spanish-speaking world.”
— Josep M. Martorell, ALIA project lead
Operational Limitations and Benchmark Performance Gaps
While ALIA-40B has been publicly released and benchmarked, its performance remains below leading models like Llama 2, raising questions about its immediate operational utility. The extent to which these limitations will impact real-world adoption and integration is still unclear, as is how the model will evolve with further training and fine-tuning.
Next Steps for ALIA and European Sovereign AI Strategies
Further benchmarking, fine-tuning, and deployment of ALIA-40B are expected in the coming months. The project team anticipates expanding multilingual capabilities and industry integration, while policymakers will monitor its adoption and operational impact. Additionally, Spain’s ongoing investment and collaboration with European partners will shape the region’s broader sovereignty efforts in AI.
Key Questions
What is the main goal of ALIA?
ALIA aims to promote widespread adoption of AI within the Spanish-speaking world, focusing on regional relevance, openness, and sovereignty rather than achieving top benchmark performance.
How does ALIA compare to other models like Llama 2?
Benchmark results show that ALIA-40B performs below Llama 2 on key NLP tasks, indicating a capability gap. However, ALIA emphasizes operational relevance and regional deployment over raw performance.
What is the significance of the public funding for ALIA?
The €240 million investment underscores Spain’s strategic commitment to developing sovereign AI infrastructure, aiming to foster regional innovation, transparency, and independence from foreign models.
Will ALIA be used outside Spain?
While designed primarily for the Spanish-speaking world, ALIA’s open-source license and multilingual capabilities could enable broader regional use, though its primary focus remains within Spain and Europe.
What are the future plans for ALIA?
Plans include further training, fine-tuning, and deployment to enhance multilingual support and industry integration, with ongoing assessment of operational impact and performance improvements.
Source: ThorstenMeyerAI.com
