The top 4 hugging face models & datasets measured by RiseFinder over the 1d window ending 15 October 2026.
MiniCPM-V 4.7 is a vision-language model from the MiniCPM-V series, released in a 1B variant. It handles single-image, multi-image, and video understanding, and combines foundation capabilities with efficient visual encoding and on-device inference, meaning it can run on local devices rather than only in the cloud.
Hugging Face model
Open source ↗This repository hosts a GGUF quantized version of MiniCPM-V 4.7 35B-A3B, a model from OpenBMB. GGUF is a format used with llama.cpp, and quantization reduces the model's size so it can run on more modest hardware. The original BF16 weights and the full model card are available in the separate openbmb/MiniCPM-V-4.7-35B-A3B repository.
Hugging Face model
Open source ↗d3-flash is a 9B multimodal foundation decision model that is part of Decision 3.0, the decision models of vLLM Semantic Router. It accepts text or JSON input, optionally with images and videos, along with a question to answer. It is built for structured decision tasks such as picking one of several options, answering yes or no, or rating on a scale.
Hugging Face model
Open source ↗vllm-sr/d3 is a 27B multimodal foundation decision model, part of Decision 3.0, the decision models of vLLM Semantic Router. It takes an input in text or JSON form, optionally with images and videos, together with questions to answer. It can pick one of several options, say yes or no, or rate on a scale, and answers all of the questions it is given.
Hugging Face model
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