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BOSS Zhipin's foundation model team Nanbeige has released the open-weight reasoning model Nanbeige4.3-33B. The model uses the Apache 2.0 license, has 33B dense parameters, supports only text input and output, has a context window of 524K tokens, and is small enough to run locally on a laptop. On the Artificial Analysis Intelligence Index v5, Nanbeige4.3-33B scores 20, on par with Qwen3.8 27B (xhigh); it scores 30% on Terminal-Bench 4.0 and 16% on the CritPt v2 Hard Subset, both higher than Qwen3.8 27B's 6% and 4%. However, it trails on AA-Briefcase v1.1 (1162 vs. 1391 Elo), FrontierCode 2.0 (11% vs. 15%), and HLE-Diamond (7% vs. 15%), and consumes about 158K output tokens per Intelligence Index task, roughly 44% more than Qwen3.8 27B's 110K. Its hallucination rate is 18% and its refusal rate is 71%. There is currently no confirmed public first-party or third-party API.
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Artificial Analysis
BOSS Zhipin's Nanbeige Releases Nanbeige4.3-33B Open-Source Reasoning Model
Nanbeige, the foundation model team under BOSS Zhipin, has released Nanbeige4.3-33B under the Apache 2.0 open-source license, featuring 33B dense parameters, text-only input and output, and a 524K token context window, small enough to run locally on a laptop. The model scores 20 on the Artificial Analysis Intelligence Index v5, on par with Qwen3.8 27B (xhigh), and achieves 30% on Terminal-Bench 4.0 and 16% on CritPt v2 Hard Subset, both higher than the latter's 6% and 4%. However, it trails on AA-Briefcase v1.1 (1162 vs. 1391 Elo), FrontierCode 2.0 (11% vs. 15%), and HLE-Diamond (7% vs. 15%), and outputs about 158K tokens per task, roughly 44% more than Qwen3.8 27B's 110K; there is currently no confirmed public API.
Nov 5
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BOSS Zhipin's Nanbeige Releases Nanbeige4.3-33B, Intelligence…
Nanbeige, the foundation model team under BOSS Zhipin, has released the open-weight reasoning model Nanbeige4.3-33B, which scores 20 on the Artificial Analysis Intelligence Index v5, on par with Qwen3.8 27B (xhigh). The model has 33B dense parameters, an Apache 2.0 license, text-only input and output, and a 524K token context window, and is small enough to run locally on a laptop. It scores 30% on Terminal-Bench 4.0 and 16% on CritPt v2 Hard Subset, both higher than Qwen3.8 27B's 6% and 4%; however, it scores 1162 Elo on AA-Briefcase v1.1, 11% on FrontierCode 2.0, and 7% on HLE-Diamond, lower than the latter's 1391, 15%, and 15%. Its hallucination rate is 18% and its refusal rate is 71%, and it consumes 158K output tokens per Intelligence Index task, about 44% more than Qwen3.8 27B's 110K. There is currently no confirmed public first-party or third-party API.