Seed-OSS 36B Instruct

Seed-OSS is a series of open-source large language models developed by ByteDance's Seed Team, designed for powerful long-context, reasoning, agent, and general capabilities alongside versatile developer-friendly features. Despite being trained on 12T tokens, Seed-OSS achieves strong performance across several popular open benchmarks. Seed-OSS-36B-Instruct is the instruction-tuned chat model in the series and is primarily optimized for international (i18n) use cases.

Key Features

• Flexible control of thinking budget - Users can dynamically adjust the reasoning length to match the task, trading extra chain-of-thought for accuracy on hard problems or shorter responses for simple ones. This lets you tune inference efficiency in production.
• Enhanced reasoning capability - Specifically optimized for reasoning tasks while maintaining balanced, strong general capabilities.
• Agentic intelligence - Performs well on agentic tasks such as tool use and issue resolving.
• Native long context - Trained natively with context lengths of up to 512K tokens.

Thinking Budget

Seed-OSS lets you specify how many tokens the model may spend on its internal reasoning before answering. With no budget set, the model thinks with unlimited length by default. When a budget is specified, the model periodically reflects on how much of the budget it has consumed and delivers its final response once the budget is exhausted or the reasoning naturally concludes. The team recommends budget values that are integer multiples of 512 (for example 512, 1K, 2K, 4K, 8K, or 16K), since the model was extensively trained on these intervals; a budget of 0 produces a direct answer with no visible reasoning.

Architecture

Seed-OSS adopts a causal language model architecture with rotary position embeddings (RoPE), grouped-query attention (GQA), RMSNorm normalization, and SwiGLU activations. This design supports its native long-context training and efficient inference at extended sequence lengths.

Benchmarks

According to the publisher's reported results, Seed-OSS-36B-Instruct is competitive across reasoning, math, coding, agentic, and long-context evaluations. It performs strongly on math and reasoning suites such as AIME and BeyondAIME, on coding benchmarks including LiveCodeBench, on instruction-following evaluations like IFEval, and on long-context retrieval tasks such as RULER at extended sequence lengths. On challenging tasks the model's chain of thought lengthens and accuracy improves as the thinking budget grows, while simpler tasks reach strong scores with shorter reasoning.

Use Cases

• Interactive chatbots and virtual assistants
• Long-document analysis, summarization, and retrieval over large contexts
• Agentic workflows involving tool use and multi-step problem solving
• Math, reasoning, and coding assistance
• Research on reasoning and post-training behavior

Deploy Seed-OSS 36B Instruct on Vast.ai to serve an OpenAI-compatible API with vLLM or run quantized GGUF builds with llama.cpp. For full model details, see the model card on HuggingFace.