Seed-2.0-pro

Seed 2 Pro is a flagship all-purpose general model designed for complex reasoning and long-chain task execution in the Agent era. It emphasizes multimodal understanding, long-context reasoning, structured generation, and tool-augmented execution. It delivers outstanding performance in handling complex instructions and multi-constraint execution, and can reliably address scenarios such as multi-step complex planning, sophisticated visual-text reasoning, video content understanding, and high-difficulty analysis.

Upgraded enterprise-grade Agent orchestration and delivery capabilities: For knowledge-intensive workflows, complex retrieval, tool invocation, and multi-step tasks can be automatically orchestrated and delivered reliably; coding capabilities have become further “agentized,” with additional optimization for the agent-oriented coding version, covering engineering decomposition and end-to-end application development.

More reliable execution of complex instructions: Instruction-following performance has been improved, along with stronger understanding and execution of multi-constraint, multi-step, and long-chain tasks, providing the foundation needed to support high-value tasks.

Upgraded multimodal understanding and reasoning: Visual perception, visual reasoning, and spatial understanding have all been significantly enhanced, enabling more stable parsing of unstructured inputs such as complex-layout documents, charts, and graphics; multimodal long-context fusion is also stronger, supporting higher-fidelity structured output.

Upgraded long-video and real-time video stream capabilities: Supports coherent understanding and high-precision reasoning over hour-long videos, and offers streaming real-time analysis and proactive feedback capabilities, enabling an interaction upgrade from passive Q&A to proactive guidance.

Adaptation for high-frequency ToB tasks and vertical scenarios: Overall capabilities have been improved for high-frequency enterprise workflows such as information extraction, reference-based Q&A, and text analysis; usability in vertical domains is further enhanced through long-tail domain knowledge and multi-source information fusion, covering more complex data processing, analysis, and customer service Agent tasks.

Flexibly control the granularity of visual unstanding tasks: Offers tiered quality–budget options of the vision input (low, high, xhigh) to balance cost and fidelity. The default high tier improves predictability, while xhigh tier handles dense text, complex charts, and detail-rich scenes more reliably.