
Seed-OSS is a set of open-source large-scale language models developed by ByteDance Seed Team, designed to provide powerful capabilities in long-context understanding, reasoning, and agentic tasks. It stands out with its flexible control of the "thinking budget", robust performance on various benchmarks, and research-friendly approach, making it a versatile tool for developers and researchers alike.
- Specifically designed to provide long-context understanding, reasoning, agentic, and general capabilities.
- Primarily optimized for internationalized (i18n) use cases.
- Users can flexibly adjust the length of reasoning as needed
- Seed-OSS is specifically optimized for reasoning tasks
According to ByteDance, the open-source SOTA (State-Of-The-Art) performs well in various categories, including Knowledge (MMLU-Pro, MMLU, TriviaQA for the base model; MMLU-Pro, MMLU for the Instruct model), Mathematics (GSM8K, MATH for the base model; AIME24, AIME25, BeyondAIME for the Instruct model), Coding (MBPP, HumanEval for the base model; LiveCodeBench v6 for the Instruct model), Instruction Following (IFEval), Agent (TAU1-Retail, SWE-Bench, Multi-SWE-Bench), Multilingualism (MMMLU), and Long Context (RULER)
Links
Seed-OSS Open-Source Models Release: https://seed.bytedance.com/en/blog/seed-oss-open-source-models-release?view_from=blogHugging Face ByteDance-Seed/Seed-OSS-36B-Instruct: https://huggingface.co/ByteDance-Seed/Seed-OSS-36B-InstructGitHub: https://github.com/ByteDance-Seed/seed-ossLM Studio: https://lmstudio.ai/home