d3-ultra decision model answers via probabilities
MarkTechPost: vLLM Semantic Router Releases d3-ultra: A 27B Open Multimodal Decision Model
The vLLM Semantic Router team has released d3-ultra, a 27B multimodal decision model under Apache-2.0. The d3-ultra decision model does not generate text. It reads an input once and returns a probability for every answer to every question. For developers, that means routing, classification, visual grounding and video checks from 1 open-weight call. TL;DR Size: 26.09B parameters (dense, including a 0.46B vision encoder); 131,072 tokens of context per question. Runs on: tested on 1 AMD
Get smart on it
d3-ultra is a 27B parameter open-source decision model that answers questions by assigning probabilities to possible answers rather than generating text. It reads input once per request and can handle multiple question types including multiple choice, yes/no, rating scales, and visual tasks like locating objects in images or tracking them in videos. The model performs best on text-based decision tasks, scoring 87.2 on the team's SR-Text benchmark, but underperforms on visual grounding tasks compared to a smaller sibling model. It can be deployed through multiple routes including self-hosting or a free API, making it available to developers who need routing, classification, and visual analysis in a single model call.
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