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Gemma 4 12B is a mid-sized member of Google DeepMind's Gemma 4 family of open-weights models. Google describes it as a unified, encoder-free multimodal model: text, images and audio are processed directly by the model rather than through separate modality encoders. Output is text.
According to creator coverage, it runs offline in around 16 GB of memory, performs close to the larger Gemma 4 24B/26B variants on benchmarks, and has been demonstrated on audio transcription and voice editing. These claims come from third-party videos and have not been verified against a model card here.
The weights are distributed under an Apache-2.0 license (the Gemma repository is Apache-2.0 licensed). Developers can use it through the JAX-based gemma library, the Google AI for Developers documentation, and the wider Gemma ecosystem for local, laptop and cloud deployment. Exact release date and detailed specifications were not in the provided material.
Watch the moment: the exact second top creators show it. Videos load only when you press play, via youtube-nocookie.com.
Open Apache 2 encoder-free multimodal model taking text, images and audio directly, runs offline in 16GB memory. Performs close to the roughly twice-larger 24B variant and shows audio transcription and voice editing.
Open-weight model that runs on a laptop and nearly matches Gemma 4 26B on benchmarks.
Closest neighbours by meaning, not just by category.
Model · Google
Google's open-weights 12B multimodal (text and image input) instruction-tuned model from the Gemma 3 family.
Model · Google
Google DeepMind's family of open-weights models built from Gemini technology, from phone-sized to laptop-class variants.
Model · Google
Google's 2B-parameter Gemma 2 instruction-tuned model, repackaged as a text encoder for PixelDiT and PiD workflows in ComfyUI.
Model · Google
Google's small open embedding model that maps text, code, images, video and audio into a shared embedding space.
Model · OpenBMB
Small open-weights multimodal model from OpenBMB for image and video understanding on phones and edge devices.
Model · Thinking Machines
Open-weights multimodal MoE model (276B total, 12B active) from Thinking Machines; text, image and audio in, text out.
