Baseten releases mammoth-1 and elephant-1 decision models
Baseten released mammoth-1 and elephant-1, open-weight models from Base Labs that return probability distributions for boolean, multiple-choice, and ordered-score questions instead of generating text. The 27B mammoth-1 and 9B elephant-1 were post-trained from Qwen3.5 models on 6.21 million examples; Baseten reports mammoth-1 first among 208 models on Jev Decision Index 0.4, while Artificial Analysis scored elephant-1 65.2, tying d1-ultra. A r/LocalLLaMA report says elephant-1 uses an MIT license and costs about $8 per million tasks, compared with roughly $31 for d1-ultra, while both models are available through Baseten Model APIs with zero data retention during the reported trial.
The release gives developers open-weight models specialized for probabilistic classification, routing, guardrails, and other decision tasks, with reported benchmark performance and serving-cost information that can be evaluated independently.
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.
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#mammoth-1#elephant-1#Baseten#Base Labs#Qwen3.5-27B#Qwen3.5-9B#d1-ultra#Artificial Analysis#Jev Decision Index 0.4