Baseten发布mammoth-1与elephant-1
Baseten发布了Base Labs训练的开放权重模型mammoth-1和elephant-1，它们不生成文本，而是为是/否、多项选择和有序评分问题返回概率分布。两款模型分别以Qwen3.5-27B和Qwen3.5-9B为基础，在621万条样本上进行后训练；Baseten称mammoth-1在Jev Decision Index 0.4的208款模型中排名第一，而Artificial Analysis给elephant-1打出65.2分，与d1-ultra并列。r/LocalLLaMA报道称，elephant-1采用MIT许可证，每百万次任务成本约8美元，而d1-ultra约为31美元；两款模型在报道所述试用期内均可通过Baseten Model API使用，并默认零数据保留。
此次发布为开发者提供了面向概率分类、请求路由和安全护栏等任务的开放权重模型，并披露了基准成绩、许可证和推理成本等可供独立评估的信息。
Published
October 21, 2026
We’re proud to release two of the world’s best decision models, trained by our own research lab: mammoth-1 (27B) and elephant-1 (9B)!
mammoth-1 ranks #1 out of 208 decision models, and elephant-1 is the leading 9B decision model on the Jev Decision Index. Both models are open-source and free to try for a week on Baseten Model APIs, with zero data retention (ZDR) by default.
✕
#mammoth-1#elephant-1#Baseten#Base Labs#Qwen3.5-27B#Qwen3.5-9B#d1-ultra#Artificial Analysis#Jev Decision Index 0.4