Nanbeige, from BOSS Zhipin, open-sources the Nanbeige4.3-33B dense model with 512K context

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😱 Unbeatable! A 30B-class open-source agent pushed to the ceiling! Nanbeige4.3-33B is officially live! It outperforms Qwen-3.8 27B! It achieves SOTA agent performance among open-source models of about 30B parameters, crushing complex coding and professional collaboration tasks across the board. It is both a ready-to-use strong teacher model and can be plugged into real agent frameworks at low cost to get work done. What makes it great: 🔹Terminal-Bench 2.1 80.9 / 4.0 23.8 / DeepSWE 65.5, leading Qwen3.8-27B and others by a wide margin on several coding agent benchmarks 🔹Leads across collaboration tasks such as Automation Bench, JobBench and DeepPlanning, covering real workplace scenarios in many industries 🔹512K ultra-long context + cost-efficient inference, usable directly as a teacher to distill later small models such as Nanbeige4.3-3B How to use it: 1️⃣Go straight to HF to download the model: huggingface.co/Nanbeige/Nanbeig… 2️⃣Load with Transformers (trust_remote_code=True), enable enable_thinking in the chat template (for agent scenarios, preserve_thinking=True is recommended) 3️⃣Recommended deployment: vLLM / SGLang + --reasoning-parser qwen3 --tool-call-parser qwen3_coder; for agent tasks temp=1.0, top_p=0.95 4️⃣Plug it into your agent framework (OpenClaw or any mainstream harness works) and start on real tasks #LLM #Agent #开源模型 #Nanbeige #AgenticAI #30B模型 #Qwen3827B