Mystery model Elephant: 100B parameters reaches same-scale SOTA with high token efficiency

神秘模型「大象」：仅100B拿下SOTA，Token效率超高！

Ant Group's Inclusion AI team is identified as the maker of Elephant, a 100B-parameter model with 256K context and 32K output shown on OpenRouter. The post reports tests on bug fixing, summarizing a 3,000-word meeting note, and a light agent loop, plus AI BENCHY figures of about 2,500 output tokens, about 1 second average latency, and 9.6/10 consistency; the post does not disclose training details, pricing, or an official model card.

Why it matters: HKR-H/K/R all pass: a 100B model posting same-scale SOTA with token efficiency is a strong hook, and the piece includes 256K/32K, ~1s latency, 9.6/10 consistency, plus failure cases. It stays below p1 because training details, pricing, and an official model card are not disclosed