# Mobilint Model Zoo Mobilint's Model Zoo (`mblt-model-zoo`) is a curated collection of deep learning models optimized by Mobilint’s Neural Processing Units (NPUs). Designed to help developers accelerate deployment, Mobilint's Model Zoo offers access to **over 400** public, pre-trained, and pre-quantized **vision, language, and multimodal models** in `.mxq`* formats, optimized for Mobilint’s runtime. Along with performance results, we provide pre- and post-processing tools to help developers evaluate, fine-tune, and integrate the models with ease. New models are added regularly to support evolving AI workloads and customer requests. ```{seealso} To download and access the Model Zoo, [**click here**](https://github.com/mobilint/mblt-model-zoo). ``` ```{tip} To check which MXQ files are compatible with your runtime environment, refer to the [MXQ compatibility matrix](compatibility.md). ``` ## Supported Models The following is a list of models (non-exhaustive) currently available in Mobilint's Model Zoo. ### Transformer Models You can find `transformers` models available in **mblt-model-zoo** in our [HuggingFace Group Page](https://huggingface.co/mobilint). ### Vision Models #### Image Classification (ImageNet) | Model | Original Source | | --------------------- | ----------------------------------------------------------------------------------------------------------- | | AlexNet | [Link](https://docs.pytorch.org/vision/stable/models/generated/torchvision.models.alexnet.html) | | ConvNeXt\_Tiny | [Link](https://docs.pytorch.org/vision/stable/models/generated/torchvision.models.convnext_tiny.html) | | ConvNeXt\_Small | [Link](https://docs.pytorch.org/vision/stable/models/generated/torchvision.models.convnext_small.html) | | ConvNeXt\_Base | [Link](https://docs.pytorch.org/vision/stable/models/generated/torchvision.models.convnext_base.html) | | ConvNeXt\_Large | [Link](https://docs.pytorch.org/vision/stable/models/generated/torchvision.models.convnext_large.html) | | DenseNet121 | [Link](https://docs.pytorch.org/vision/stable/models/generated/torchvision.models.densenet121.html) | | DenseNet169 | [Link](https://docs.pytorch.org/vision/stable/models/generated/torchvision.models.densenet169.html) | | DenseNet201 | [Link](https://docs.pytorch.org/vision/stable/models/generated/torchvision.models.densenet201.html) | | GoogLeNet | [Link](https://docs.pytorch.org/vision/stable/models/generated/torchvision.models.googlenet.html) | | Inception\_V3 | [Link](https://docs.pytorch.org/vision/main/models/generated/torchvision.models.inception_v3.html) | | MNASNet1\_0 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.mnasnet1_0.html) | | MNASNet1\_3 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.mnasnet1_3.html) | | MobileNet\_V2 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.mobilenet_v2.html) | | RegNet\_X\_400MF | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.regnet_x_400mf.html) | | RegNet\_X\_800MF | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.regnet_x_800mf.html) | | RegNet\_X\_1\_6GF | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.regnet_x_1_6gf.html) | | RegNet\_X\_3\_2GF | [Link](https://docs.pytorch.org//vision/2.0/models/generated/torchvision.models.regnet_x_3_2gf.html) | | RegNet\_X\_8GF | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.regnet_x_8gf.html) | | RegNet\_X\_16GF | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.regnet_x_16gf.html) | | RegNet\_X\_32GF | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.regnet_x_32gf.html) | | RegNet\_Y\_400MF | [Link](https://docs.pytorch.org/vision/stable/models/generated/torchvision.models.regnet_y_400mf.html) | | RegNet\_Y\_800MF | [Link](https://docs.pytorch.org/vision/stable/models/generated/torchvision.models.regnet_y_800mf.html) | | RegNet\_Y\_1\_6GF | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.regnet_y_1_6gf.html) | | RegNet\_Y\_3\_2GF | [Link](https://docs.pytorch.org//vision/2.0/models/generated/torchvision.models.regnet_y_3_2gf.html) | | RegNet\_Y\_8GF | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.regnet_y_8gf.html) | | RegNet\_Y\_16GF | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.regnet_y_16gf.html) | | RegNet\_Y\_32GF | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.regnet_y_32gf.html) | | ResNet18 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.resnet18.html) | | ResNet34 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.resnet34.html) | | ResNet50 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.resnet50.html) | | ResNet101 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.resnet101.html) | | ResNet152 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.resnet152.html) | | ResNeXt50\_32X4D | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.resnext50_32x4d.html) | | ResNeXt101\_32X8D | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.resnext101_32x8d.html) | | ResNeXt101\_64X4D | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.resnext101_64x4d.html) | | ShuffleNet\_V2\_X1\_0 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.shufflenet_v2_x1_0.html) | | ShuffleNet\_V2\_X1\_5 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.shufflenet_v2_x1_5.html) | | ShuffleNet\_V2\_X2\_0 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.shufflenet_v2_x2_0.html) | | VGG11 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.vgg11.html) | | VGG11\_BN | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.vgg11_bn.html) | | VGG13 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.vgg13.html) | | VGG13\_BN | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.vgg13_bn.html) | | VGG16 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.vgg16.html) | | VGG16\_BN | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.vgg16_bn.html) | | VGG19 | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.vgg19.html) | | VGG19\_BN | [Link](https://docs.pytorch.org//vision/stable/models/generated/torchvision.models.vgg19_bn.html) | | Wide\_ResNet50\_2 | [Link](https://docs.pytorch.org/vision/stable/models/generated/torchvision.models.wide_resnet50_2.html) | | Wide\_ResNet101\_2 | [Link](https://docs.pytorch.org/vision/stable/models/generated/torchvision.models.wide_resnet101_2.html) | #### Object Detection (COCO) | Model | Original Source | | ----------- | --------------------------------------------------- | | yolov3u | [Link](https://docs.ultralytics.com/models/yolov3/) | | yolov3-spp | [Link](https://github.com/ultralytics/yolov3/) | | yolov3-sppu | [Link](https://docs.ultralytics.com/models/yolov3/) | | yolov5su | [Link](https://docs.ultralytics.com/models/yolov5/) | | yolov5mu | [Link](https://docs.ultralytics.com/models/yolov5/) | | yolov5lu | [Link](https://docs.ultralytics.com/models/yolov5/) | | yolov5l6 | [Link](https://github.com/ultralytics/yolov5/) | | yolov5xu | [Link](https://docs.ultralytics.com/models/yolov5/) | | yolov5x6 | [Link](https://github.com/ultralytics/yolov5/) | | yolov7 | [Link](https://github.com/WongKinYiu/yolov7/) | | yolov7x | [Link](https://github.com/WongKinYiu/yolov7/) | | yolov8s | [Link](https://docs.ultralytics.com/models/yolov8/) | | yolov8m | [Link](https://docs.ultralytics.com/models/yolov8/) | | yolov8l | [Link](https://docs.ultralytics.com/models/yolov8/) | | yolov8x | [Link](https://docs.ultralytics.com/models/yolov8/) | | yolov9m | [Link](https://github.com/WongKinYiu/yolov9/) | | yolov9c | [Link](https://github.com/WongKinYiu/yolov9/) | | yolo11s | [Link](https://docs.ultralytics.com/models/yolo11/) | | yolo11m | [Link](https://docs.ultralytics.com/models/yolo11/) | | yolo11l | [Link](https://docs.ultralytics.com/models/yolo11/) | | yolo11x | [Link](https://docs.ultralytics.com/models/yolo11/) | | yolo12s | [Link](https://docs.ultralytics.com/models/yolo12/) | | yolo12m | [Link](https://docs.ultralytics.com/models/yolo12/) | #### Instance Segmentation (COCO) | Model | Original Source | | ----------- | --------------------------------------------------- | | yolov5l-seg | [Link](https://github.com/ultralytics/yolov5/) | | yolov5x-seg | [Link](https://github.com/ultralytics/yolov5/) | | yolov8s-seg | [Link](https://docs.ultralytics.com/models/yolov8/) | | yolov8m-seg | [Link](https://docs.ultralytics.com/models/yolov8/) | | yolov8l-seg | [Link](https://docs.ultralytics.com/models/yolov8/) | | yolov8x-seg | [Link](https://docs.ultralytics.com/models/yolov8/) | | yolov9c-seg | [Link](https://docs.ultralytics.com/models/yolov9/) | | yolo11s-seg | [Link](https://docs.ultralytics.com/models/yolo11/) | | yolo11m-seg | [Link](https://docs.ultralytics.com/models/yolo11/) | | yolo11l-seg | [Link](https://docs.ultralytics.com/models/yolo11/) | | yolo11x-seg | [Link](https://docs.ultralytics.com/models/yolo11/) |