InfantAgent-Next: A Multimodal Generalist Agent for Automated Computer Interaction

InfantAgent-Next is a multimodal AI agent that combines tool-based and vision-based approaches in a modular architecture to interact with computers across text, images, audio, and video. The system achieves 7.27% accuracy on OSWorld benchmarks, outperforming Claude's Computer Use, and demonstrates broad applicability across vision-based and general benchmarks.

InfantAgent-Next represents a meaningful advancement in autonomous computer interaction by addressing a key limitation of existing approaches: the choice between monolithic single-model workflows and purely modular systems. The architecture enables different specialized models to tackle decoupled subtasks sequentially, allowing the system to leverage both vision-based reasoning and tool-specific interactions where each excels.

The development of general-purpose AI agents capable of autonomous computer use has accelerated significantly since late 2024, with multiple organizations racing to create systems that can navigate complex digital environments. InfantAgent-Next distinguishes itself through architectural modularity and multimodal capability spanning text, images, audio, and video processing. This broader input spectrum positions the agent to handle more diverse real-world scenarios than single-modality predecessors.

The benchmark results carry notable implications for the AI development community. Outperforming Claude Computer Use on OSWorld suggests the modular approach yields practical advantages despite apparent complexity. However, the 7.27% absolute accuracy indicates substantial room for improvement before deployment in high-stakes scenarios. The ability to evaluate across heterogeneous benchmarks (OSWorld for vision tasks, GAIA for reasoning, SWE-Bench for software engineering) demonstrates genuine generalization rather than benchmark-specific optimization.

As autonomous agent capabilities mature, the modularity demonstrated here may influence industry standards. The open-source release accelerates community iteration and adoption. Future developments will likely focus on improving accuracy rates and reducing latency for production deployment. The competition between monolithic and modular approaches will determine which architectural philosophy dominates next-generation agent development.

• →InfantAgent-Next outperforms Claude Computer Use with 7.27% accuracy on OSWorld benchmarks using a modular multi-agent architecture.
• →The system integrates tool-based agents and vision agents working collaboratively, enabling cross-modal reasoning across text, images, audio, and video.
• →Evaluation across diverse benchmarks (OSWorld, GAIA, SWE-Bench) demonstrates genuine generalization beyond single-domain optimization.
• →Modular architecture allows specialized models to handle decoupled subtasks, representing a potential shift from monolithic AI agent design.
• →Open-source release accelerates community development of autonomous computer interaction systems.