Nanbeige LLM Lab has released Nanbeige4.3-33B on Hugging Face under the Apache 2.0 license. Nanbeige4.3-33B is a 33B dense language model built for agentic coding and office-style "cowork" tasks. The lab sits inside the recruitment platform BOSS Zhipin. It also published Nanbeige4.3-33B-Base for custom post-training. The model supports a 524,288-token context window. In the lab's own table, it leads 17 of 20 benchmarks against three open models near 30B.
TL;DR
- Size: 33B parameters, dense (no MoE), 524,288-token (512K) context, BF16 weights.
- Runs on: Multi-GPU servers. The card's SGLang and vLLM recipes use 4-way tensor parallelism. BF16 weights need about 66 GB (our arithmetic). One community quantization is listed.
- Performance: Leads 17 of 20 rows in Nanbeige's own comparison against Qwen3.8-27B, Muse-Glimmer-30B and Gemma4-31B.
- Best: 80.9 on Terminal-Bench 2.1, versus 73.0 for Qwen3.8-27B.
- Worst: 23.8 on Terminal-Bench 4.0 (its lowest score). It also trails Qwen3.8-27B on SWE-Bench Pro, 60.3 vs 61.7.
What is Nanbeige4.3-33B?
Nanbeige4.3-33B is the flagship "teacher" model of the Nanbeige4.3 series. The lab's release positions it as a self-contained agentic coding model rather than a general-purpose chatbot, pairing a large context window with tool-use and terminal-oriented benchmarks. As of 2026, the open-weight landscape around 30B has grown crowded—Qwen3.8-27B, Muse-Glimmer-30B and Gemma4-31B all compete in roughly the same hardware envelope—so Nanbeige's claims rest on its own comparative table rather than independent evaluation. The Apache 2.0 license and companion Base checkpoint make it straightforward to fine-tune for downstream agentic workflows.
via MarkTechPost