Seed1.8 Model Card: Towards Generalized Real-World Agency

Computer Science > Artificial Intelligence [Submitted on 21 Mar 2026] Seed1.8 Model Card: Towards Generalized Real-World Agency Bytedance Seed We present Seed1.8, a foundation model aimed at generalized real-world agency: going beyond single-turn prediction to multi-turn interaction, tool use, and multi-step execution. Seed1.8 keeps strong LLM and vision-language performance while supporting a unified agentic interface-search, code generation and execution, and GUI interaction. For deployment, it offers latency- and cost-aware inference, including configurable thinking modes and optimized visual encoding for images and video. We report evaluations on standard benchmarks and application-aligned workflows spanning foundational skills, multimodal understanding, and agentic behavior. Seed1.8 is released to support further research and development on interactive, real-world use cases. Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2603.20633 [cs.AI]   (or arXiv:2603.20633v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2603.20633 Focus to learn more Submission history From: Yujia Qin [view email] [v1] Sat, 21 Mar 2026 04:03:45 UTC (6,596 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-03 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)