Decision Models / Mammoth 1
OPEN
Mammoth 1
By Baseten (Base Labs) · Released 21 Oct 2026
Two open decision models from Base Labs, Baseten's research team: mammoth-1 (27B) and elephant-1 (9B), post-trained from Qwen3.5. They read text and images and return a probability for every option of each question, with all questions sharing one prefill of the state. Baseten launched them claiming the top spot on the community Jev Decision Index. On 29 Oct a third, smaller model joined: joey-1 (2B, built on Qwen3.5-2B), pitched as the fastest and cheapest.
Facts
- Sizes
- mammoth-1 27B (Qwen3.5-27B), elephant-1 9B (Qwen3.5-9B) and joey-1 2B (Qwen3.5-2B), 16,384-token context
- Licence
- MIT
- Price
- OpenRouter lists mammoth-1 at $0.10, elephant-1 at $0.035 and joey-1 at $0.01 per million input tokens, output free (as of 30 Oct 2026) · Compare prices
Claims and sources
- Baseten says mammoth-1 ranked #1 of 208 models on Jev Decision Index 0.4 with a full score of 71.24, and elephant-1 is the best decision model under 15B parameters (62.65) vendor reportedsource
- In the index's current public data (Decision Index 0.4.1, generated 22 Oct 2026), mammoth-1 is first of 228 on both public-benchmark scores (75.34 skill, 81.19 raw) but third on the full score (68.44), behind GLiDE v1.2 (71.52) and jeffan-31b (69.75) independentsource
- Baseten says joey-1 has a P50 latency of 20 ms, 5x faster than comparable decision models vendor reportedsource
Links
Source: Announcement → Source: Technical report → Source: mammoth-1 on Hugging Face → Source: elephant-1 on Hugging Face → Source: joey-1 →
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