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arxiv:2603.20633

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

Published on Apr 17
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Abstract

Seed1.8 is a foundation model that extends beyond single-turn prediction to support multi-turn interaction, tool use, and multi-step execution while maintaining strong language and vision-language capabilities.

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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.

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