CogAgent is a 9B-parameter bilingual vision-language GUI agent model based on GLM-4V-9B, trained with staged data curation, optimization, and strategy upgrades to improve perception, action prediction, and generalization across tasks. It focuses on operating real user interfaces from screenshots plus text, and follows a strict input–output format that returns structured actions, grounded operations, and optional sensitivity annotations. The model is designed for agent-style execution rather than freeform chat, maintaining a continuous execution history across steps while requiring a fresh session for each new task. Inference supports BF16 on NVIDIA GPUs, with optional INT8 and INT4 modes available but with noted performance loss at INT4; example CLIs and a web demo illustrate bounding-box outputs and operation categories.
Features
- Bilingual GUI agenting in Chinese and English with screenshots as input
- Strict, platform-aware prompting for WIN, Mac, and Mobile targets
- Structured outputs with Action, Operation, Status, Plan, and sensitivity modes
- Bounding-box grounded operations for precise UI localization
- CLI and web demos for local inference with saved overlay results
- SFT and LoRA fine-tuning recipes with detailed GPU and token budgets