sophnet/Seed-OSS-36B-Instruct

Seed-OSS-36B-Instruct is an open-source instruction-tuned large language model released by ByteDance’s Seed team. Its core positioning is as a versatile productivity foundation characterized by “native long-context capabilities, high inference efficiency, and strong agent-like abilities.”

• Native ultra-long context of 512K tokens: Without the need for external extension mechanisms, it directly supports input lengths of up to 512,000 tokens, delivering stable performance in long-text tasks such as “needle-in-a-haystack” scenarios.
• Flexible control over reasoning budget: Users can dynamically adjust the inference length, achieving a fine balance between cost and performance.
• Enhanced inference and agent capabilities: It significantly outperforms same-size open-source models in scenarios such as mathematics, code generation, tool calls, and multi-step task planning, making it well-suited for agent-based applications.
• High-quality training on 12T tokens: Trained on massive, multi-stage datasets, it strikes a good balance between general-purpose capabilities and specialized tasks.

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Core Capabilities

🧠 Deep multi-step reasoning: When faced with complex problems, it can autonomously break them down into smaller steps and solve them sequentially while maintaining logical consistency across long contexts.

🧩 Agent-ready architecture: Natively supports function calls, environment interactions, and result integration, making it an ideal core decision-making engine for AI agents.

⚡ Efficient real-world performance: Even on low-cost hardware, it maintains excellent response speeds, making it suitable for enterprise-level deployment scenarios.

📚 Well-balanced general capabilities: In multi-dimensional evaluations including C-Eval, MMLU, GSM8K, and HumanEval, its performance approaches or reaches the best levels among comparable open-source models.