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Techniquesmodel architecturemultimodal architecture

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Encoder-free multimodal architecture

Audio and vision inputs are incorporated without separate modality encoders, with raw inputs projected directly into the language-model embedding space.

Also called Encoder-free decoder-only architecture, encoder-free architecture, encoder-free multimodal input projection.

sources
6
models
2
labs adopt it
2
strongest
core

How sources treat it

One count per evidence span, weakest treatment to strongest.

used 2core 4

Documented in

Further reading

Picked by hand, not extracted: where to read more, not evidence for anything on this page.

Evidence

6 spans quoted from the sources, strongest treatment first.

This unified approach means all modalities flow straight into a single decoder-only transformer

coremodel architecturein Gemma 4Google DeepMind

we trained Gemma 4 12B with an encoder-free architecture to integrate audio and vision input directly.

coremodel architecturein Gemma 4 12BGoogle

Gemma 4 12B eliminates these encoders entirely, projecting raw image patches and audio waveforms directly into the LLM's embedding space through lightweight linear layers.

coremodel architecturein Gemma 4Google DeepMind

Gemma 4 12B eliminates these encoders entirely, projecting raw image patches and audio waveforms directly into the LLM's embedding space through lightweight linear layers.

coremodel architecturein Gemma 4Google DeepMind

We introduce a unified encoder-free architecture for the 12B model, which projects raw 40ms audio chunks and image patches into the LLM embedding space, alleviating the need for separate encoders and reducing memory fragmentation.

usedmodel architecturein Gemma 4 12BGoogle DeepMind

We opted for an encoder-free architecture for audio and vision inputs, consistent with the interaction model design.

usedmodel architecturein InklingThinking Machines Lab

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Other methods under model architecture :: multimodal architecture.