Surfer-H Meets Holo1: Cost-Efficient Web Agent Powered by Open Weights
Authors: name: Mathieu Andreux; name: Breno Baldas Skuk; name: Hamza Benchekroun; name: Emilien Biré; name: Antoine Bonnet; name: Riaz Bordie; name: Matthias Brunel; name: Pierre-Louis Cedoz; name: Antoine Chassang; name: Mickaël Chen; name: Alexandra D. Constantinou; name: Antoine d'Andigné; name: Hubert de La Jonquière; name: Aurélien Delfosse; name: Ludovic Denoyer; name: Alexis Deprez; name: Augustin Derupti; name: Michael Eickenberg; name: Mathïs Federico; name: Charles Kantor; name: Xavier Koegler; name: Yann Labbé; name: Matthew C. H. Lee; name: Erwan Le Jumeau de Kergaradec; name: Amir Mahla; name: Avshalom Manevich; name: Adrien Maret; name: Charles Masson; name: Rafaël Maurin; name: Arturo Mena; name: Philippe Modard; name: Axel Moyal; name: Axel Nguyen Kerbel; name: Julien Revelle; name: Mats L. Richter; name: María Santos; name: Laurent Sifre; name: Maxime Theillard; name: Marc Thibault; name: Louis Thiry; name: Léo Tronchon; name: Nicolas Usunier; name: Tony Wu
Published: 2025-06-03 13:29:03

Abstract: We present Surfer-H, a cost-efficient web agent that integrates
Vision-Language Models (VLM) to perform user-defined tasks on the web. We pair
it with Holo1, a new open-weight collection of VLMs specialized in web
navigation and information extraction. Holo1 was trained on carefully curated
data sources, including open-access web content, synthetic examples, and
self-produced agentic data. Holo1 tops generalist User Interface (UI)
benchmarks as well as our new web UI localization benchmark, WebClick. When
powered by Holo1, Surfer-H achieves a 92.2% state-of-the-art performance on
WebVoyager, striking a Pareto-optimal balance between accuracy and
cost-efficiency. To accelerate research advancement in agentic systems, we are
open-sourcing both our WebClick evaluation dataset and the Holo1 model weights.