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f-inference

ABOUT / THE PROJECT

A different way to deploy intelligence.

The f-inference project is making foundation models more efficient, inclusive and sovereign across cloud, edge and IoT.

INSIDE THE PROJECT

Why a new approach is needed

Foundation models can work with language, images, audio, video and time-series data. Yet many deployments still rely on remote cloud infrastructures.

This dependence creates challenges: sensitive information may leave organisational boundaries; specialised computing raises costs and energy demand; and remote processing can add latency to time-critical services.

THE RESEARCH CHALLENGE

Four limitations to overcome.

01 / DIGITAL SOVEREIGNTY

Keep data in your control

Run models where sensitive data is generated, reducing reliance on external infrastructure.

02 / ENERGY EFFICIENCY

Smaller footprint. Smarter inference.

Reduce energy through model optimisation and resource-aware placement.

03 / ACCESSIBILITY

Powerful AI for more organisations

Bring efficient foundation models within reach of SMEs and resource-limited settings.

04 / LOW LATENCY

Real-time intelligence

Move inference closer to people, machines and sensors for responsive applications.

THE VISION

Our vision

f-inference envisions a Resource-driven Computing Continuum (RCC) spanning cloud, edge and IoT. Models can be distributed, adapted and coordinated across these tiers instead of running only in distant data centres.

The goal is to place intelligence as close as practical to the sources of data and the people who use it, balancing performance, security, energy use, affordability and ownership of data.

WHAT WE WILL DELIVER
01

Optimisation strategies

Design-time profiling, compression and device-aware model adaptation.

02

Adaptive inference

Distributed inference, routing, caching and cross-platform execution.

03

An open framework

Deployment pipelines and policy-aware orchestration across the continuum.

04

Open research results

Open tools, datasets, academic publications and policy recommendations.

Project at a glance.

A Research and Innovation Action supported by the European Union.

Field

Value

Full title


Efficient Foundation Model Inference Across the Computing Continuum

Grant Agreement

101298393

Programme

Horizon Europe, Cluster 4 (Digital, Industry and Space)

Topic

HORIZON-CL4-2025-04-DATA-02

Type of action

Research and Innovation Action (RIA)

Duration

1 October 2026 – 30 September 2029 (36 months)

Coordinator

Institute of Communication and Computer Systems (ICCS), Greece

EU contribution

€7,984,003.75

Granting authority

European Health and Digital Executive Agency (HaDEA)