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DeepSeek ViT

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DeepSeek ViT

Category: Encoder Β· Code: timm/models/deepseek_vit.py Β· Architectures: 3 Β· Pretrained weights: 6 (0 with ImageNet-1k results)

The vision encoder of the DeepSeek-V4 / V4.1 multimodal models, a pre-norm ViT with RMSNorm, a SwiGLU MLP and axial 2D RoPE as the only position encoding. Classifier variants add pooling and a linear head, the _enc variants keep the native projector that maps the tokens to the language model width.

Papers

Usage

See the Quickstart for loading pretrained weights, image preprocessing and fine-tuning, and Feature Extraction for using the models as backbones.

>>> import timm
>>> model = timm.create_model('deepseek_vit_412m.deepseek_v4_1_flash', pretrained=True)
>>> data_config = timm.data.resolve_model_data_config(model)

Model API support

FeatureDeepseekVitClassifierDeepseekVitEncoder
features_only=True feature mapsβœ“ (strides 14, 14, 14)βœ“ (strides 14, 14, 14)
forward_intermediates()βœ“βœ“
prune_intermediate_layers()βœ“βœ“
Any input size, no changes neededβœ“βœ“
set_input_size()––
dynamic_img_size=True––
set_grad_checkpointing()βœ“βœ“
Layer-wise LR decay (group_matcher())βœ“βœ“
reset_classifier()βœ“βœ—

βœ“ supported, βœ“ (square) works for square sizes only, βœ— not supported, – not needed (the model already accepts any input size). Checked by running each feature on a randomly initialized model (DeepseekVitClassifier with deepseek_vit_412m at 252, DeepseekVitEncoder with deepseek_vit_412m_enc at 252), other architectures of the same class are expected to behave the same. See the Model API page for details.

Architectures

ArchitectureClassParams (M)GMACsInput sizePretrained weights
deepseek_vit_412mDeepseekVitClassifier411.84-5462
deepseek_vit_412m_alignDeepseekVitClassifier485.25-5462
deepseek_vit_412m_encDeepseekVitEncoder485.25-5462

GMACs and parameter counts are for the default input size and classifier of each architecture, from the benchmark results.

Pretrained weights

Top-1 is ImageNet-1k validation accuracy from results-imagenet.csv at the listed eval size, - if the weight has no ImageNet-1k result (e.g. pretraining or image-text weights). Classes is the size of the pretrained classifier, none for weights without one.

Weights are grouped by source: the paper or origin given in the pretrained config, else a Hub organization other than timm, else the first part of the pretrained tag (architecture.tag). Sources with a single weight are listed under other.

deepseek-ai/DeepSeek-V4-Flash-Vision-Exp

Origin: huggingface.co/deepseek-ai/DeepSeek-V4-Flash-Vision-Exp

WeightInput sizeTop-1 (%)Eval sizeClassesLicenseHub
deepseek_vit_412m.deepseek_v4_flash_vision_exp392--nonemittimm
deepseek_vit_412m_align.deepseek_v4_flash_vision_exp392--nonemittimm
deepseek_vit_412m_enc.deepseek_v4_flash_vision_exp392--nonemittimm

deepseek-ai/DeepSeek-V4.1-Flash

Origin: huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash

WeightInput sizeTop-1 (%)Eval sizeClassesLicenseHub
deepseek_vit_412m.deepseek_v4_1_flash546--nonemittimm
deepseek_vit_412m_align.deepseek_v4_1_flash546--nonemittimm
deepseek_vit_412m_enc.deepseek_v4_1_flash546--nonemittimm
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