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OpenBMB Releases MiniCPM-V 4.7 in 35B-A3B and 1B Variants

10/13/2026 — 10/13, 18:23·2 sources (all)·3 reports (all)

Key takeaways

  • OpenBMB has released MiniCPM-V 4.7, a new on-device multimodal model family available in two variants: a 35B-A3B MoE version and a 1B versio…

Background & analysis

On October 13, 2026, openbmb released MiniCPM-V 4.7 under its MiniCPM-V series, with two variants surfacing the same day. The first report, posted at 01:16, said the series had gained a 35B-A3B version, the first MoE model in the MiniCPM-V family. It keeps the family's single-image, multi-image, and video understanding capabilities while adding stronger visual encoding and more efficient on-device inference, and its weights and gguf files were published on Hugging Face at openbmb/MiniCPM-V-4.7-35B-A3B-gguf.

Roughly 47 minutes later, at 02:03, a second report said openbmb had also released a 1B version of MiniCPM-V 4.7 aimed at on-device inference. That variant likewise builds on single-image, multi-image, and video understanding, and is described as combining stronger foundation capabilities with efficient visual encoding and on-device inference; its GGUF files were also made available at openbmb/MiniCPM-V-4.7-1B-gguf. The same report mentions a new Pareto frontier in performance and efficiency for this release.

Both posts came from LocalLLaMA and both describe MiniCPM-V 4.7 as the latest model in the MiniCPM-V series, citing the same core capabilities: single-image, multi-image, and video understanding, efficient visual encoding, and on-device inference. The available information ends with the release of these two variants, 35B-A3B and 1B, and the publication of their GGUF weights; the reports give no further updates beyond that point.

AI-generated from 2 reports · updated 17 hours ago

Latest turnModelBest has released MiniCPM-V 4.7, a new family of on-device multimodal models offered in 35B-A3B and 1B versions. The larger model uses an MoE architecture with 35B total parameters but activates only about 3B per inference; the company says it needs roughly 3GB of RAM to decode more than 15 tokens per second on an iPad Pro, and calls it the first open-source MoE model to run losslessly and smoothly on-device.

24-hour heatHeat index 153 · peak 160 · 1h ago
24 hours agonow

Reports on this story headlines open the original

Today
  1. ModelBest has released MiniCPM-V 4.7, a new family of on-device multimodal models offered in 35B-A3B and 1B versions. The larger model uses an MoE architecture with 35B total parameters but activates only about 3B per inference; the company says it needs roughly 3GB of RAM to decode more than 15 tokens per second on an iPad Pro, and calls it the first open-source MoE model to run losslessly and smoothly on-device.

    华尔街见闻AI score 62
  2. openbmb released a 1B variant of MiniCPM-V 4.7, the latest model in its MiniCPM-V series. It keeps single-image, multi-image and video understanding while pairing stronger foundation capabilities with efficient visual encoding and on-device inference, and GGUF weights are already available.

    Reddit · LocalLLaMAAI score 52
  3. openbmb has released MiniCPM-V 4.7 in a 35B-A3B variant, the first MoE model in the MiniCPM-V series. It keeps the family's single-image, multi-image, and video understanding abilities while adding stronger visual encoding and more efficient on-device inference; weights and gguf builds are available on Hugging Face.

    Reddit · LocalLLaMAAI score 62

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