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

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.