Nanbeige releases a 33-billion-parameter open model that it says beats Qwen3.8-27B at agentic coding

Nanbeige, the AI team backed by Chinese recruitment company BOSS Zhipin, has released Nanbeige4.3-33B on Hugging Face under the Apache 2.0 licence. According to the benchmark table on the model card, it beats Alibaba's Qwen3.8-27B on seven of eight agentic-coding evaluations. On DeepSWE it scores 65.5 against Qwen's 42.5, and on Terminal-Bench 2.1 it scores 80.9 against 73.0. The card also compares it with Google's Gemma4-31B and a model called Muse-Glimmer-30B, which are in roughly the same size class. Startup Fortune reports that the gaps are wider on agentic cowork benchmarks than on raw reasoning. Nanbeige calls the model the "flagship teacher model" of a planned family. It intends to distill it into smaller, cheaper versions, as it did earlier this year with its 3-billion-parameter line. The release quickly drew attention on the r/LocalLLaMA forum. All of the figures come from Nanbeige's own model card and have not been independently verified. For developers who run models on their own hardware, a permissively licensed mid-size model with strong coding-agent scores could offer a cheaper alternative to larger open models while GPU rental costs stay high.