AI Models verified for OpenVINO™#

The following is a list of models that have been verified to work with OpenVINO. Note that other models from OpenVINO-supported frameworks may also work properly but have not been tested.

AI Models that run on Intel® Core Ultra™ Processors with OpenVINO™ toolkit:

Search:

Model	Category	Framework	Precision
aclnet	Sound Classification	onnx	FP16
aclnet	Sound Classification	onnx	FP16-INT8
aclnet	Sound Classification	onnx	FP32
aclnet-int8	Sound Classification	onnx	FP16-INT8
adv_inception_v3	Image Classification	pytorch	FP32
albert-base-v2	Natural Language Processing	pytorch	intel-optimum default
albert-base-v2-sst2	Natural Language Processing	pytorch	intel-optimum default
albert-large-v2	Natural Language Processing	pytorch	intel-optimum default
albert-large-v2-finetuned-mnli	Natural Language Processing	pytorch	intel-optimum default
alexnet-caffe	Image Classification	caffe	FP16

Showing 1 to 10 of 909 entries

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Marked cells indicate models that passed inference with no errors. Empty cells indicate
models that were not tested. No failing runs producing an error have been recorded.

In the precision column, the “optimum-intel default” label corresponds to FP32 for small models
and INT8 for models greater than 1B parameters.

The results as of June 17 2024, for OpenVINO version 2024.2.
The models come from different public model repositories, such as Pytorch Model Zoo and
HuggingFace; they were executed on the designated hardware with OpenVINO either natively or
as a backend.