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The Seed LLM team is dedicated to aggressively advancing the next generation of LLMs, tackling fundamental challenges in LLM development head-on. Our areas of focus include model pretraining, posttraining, inference, memory capabilities, learning, interpretability and other related directions. We dive deep into the latest technologies and create comprehensive solutions from concept to completion. In our endeavor to adopt LLMs in real-life scenarios, we persistently seek out methods to enhance applications through technological innovation.
Latest advancements

Seed1.8

Seed1.8
通用 Agent 模型,能在复杂工作流中高效精准地完成任务

Seed1.6

Seed1.6
融合多模态能力,“自适应思考”平衡模型效果与推理性能

Seed Diffusion Preview

Seed Diffusion Preview
基于离散扩散技术的大规模语言模型,代码推理速度可达 2146 tokens/s,相比同等规模的自回归模型提升 5.4 倍

Selected papers

Aug 4, 2025
Seed Diffusion: A Large-Scale Diffusion Language Model with High-Speed Inference
Computation and Language
May 17, 2025
Model Merging in Pre-training of Large Language Models
LLM
Apr 2, 2025
Exploring Data Scaling Trends and Effects in Reinforcement Learning from Human Feedback
Machine Learning
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Featured roles

Research Scientist in Large Language Model
San Jose
Experienced Hiring
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Research Scientist, Reinforcement Learning
San Jose
Experienced Hiring
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Research Scientist in Large Language Model, Seed-PhD Graduates- 2026 Start
San Jose
Campus Recruitment
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Student Researcher [Seed LLM Post Training – Reward Modeling] - 2026 Start (PhD)
Seattle/San Jose
Internship
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Student Researcher (Seed - LLM Post-training) - 2025 Start (PhD)
Seattle/San Jose
Internship
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Infrastructures
Vision
Speech
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AI for Science
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Responsible AI
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