Multimodal open d1 decision models for the edge
Best decision model under 10B on the Decision Index 0.2.1: d1-3B scores 48.57, ahead of every 4B and 9B model and of Decider 35B-A3B (47.11).
ProofVendor claim only
Key points
- Multimodal: d1-3B supports text and images, while d1-omni-600M supports text and images or text and audio
- Fast: d1-3B answers a question in 16 ms on an NVIDIA Jetson AGX Thor, 26 ms on a Jetson AGX Orin, and 50ms on a Jetson Orin Nano
- We benchmarked d1-3B and d1-omni-600M on seven public datasets spanning reading comprehension, toxicity detection, intent classification, medical QA, and cross-lingual understanding. d1-3B achieves a mean score of 82.9, the highest in the table and above Decider 4B. d1-omni-600M scores 78.4, surpassing Decider 2B (77.1) with only a quarter of the parameters.
- Reach for d1 decision models when you need fast, structured decisions, including multimodal inputs. d1-3B delivers the highest decision quality at its size, while d1-omni-600M fits where footprint matters.
Sources (1)
- [1]Multimodal open d1 decision models for the edgeHugging Face Blog · Oct 7, 04:54 PM
- Best decision model under 10B on the Decision Index 0.2.1: d1-3B scores 48.57, ahead of every 4B and 9B model and of Decider 35B-A3B (47.11).
- Multimodal: d1-3B supports text and images, while d1-omni-600M supports text and images or text and audio
Extractive summary: sentences quoted from the sources.
Hype check
Independently evaluated2 independent looks since
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- Follow-up · Oct 7, 2026Distilling Graph Geometry: Knowledge Gap from GNNs to MLPs
Before this
- Oct 6, 2026nvidia/GLM-5.3-Flash-FP4-Local
- Oct 6, 2026EmbeddingGemma 2: an open, lightweight multimodal embedding model
- Oct 6, 2026Introducing Mistral Large 4
- Oct 6, 2026[AINews] Reflection Beam - 501B-A23B American Open Model
- Oct 1, 2026nvidia/PixelUMM
- Oct 1, 2026nvidia/PixelDiT2-ImageNet
