implementation detail · filed under model architecture
High-resolution autoregressive vision-encoder fine-tuning
Input resolution is constrained to a specified range by proportionally scaling images outside it.
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How sources treat it
One count per evidence span, weakest treatment to strongest.
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Documented in
Evidence
1 span quoted from the sources, strongest treatment first.
We therefore constrain the input resolution between 544× 544 and 1344× 1344 pixels by proportionally scaling out-of-bound images.
usedunclearin DeepSeek-V4.1-FlashDeepSeek
Filed alongside
Other methods under model architecture :: multimodal architecture.
Encoder-free multimodal architectureEarly fusion multimodal trainingDiscrete token encoding for audioHierarchical patch encoderMixed-modality trainingConfigurable visual token budgetJoint multimodal decoding in a shared hidden spaceNative multimodal understanding3×3 pixel-unshuffle downsamplingJoint vision-language pre-trainingRaw audio projection into the LLM embedding spaceVision Transformer (ViT)2×2 pixel-shuffle downsamplingAudio encoder initialized from MiMo-AudioAudio Transformer (AuT)Causal streaming ConvNet codec decoderData-parallel-first multimodal encodingDecoupled Encoder Process (DEP)Dedicated multimodal encodersDisaggregated encoder trainingDiscarding the LLM after vision-encoder trainingDual-format coordinate supervisionExplicit text-string timestampsFour-frame audio patches with within-patch bidirectional self-attention