diff --git a/docs/build/eps.md b/docs/build/eps.md
index 72ef11f829..9ed1277932 100644
--- a/docs/build/eps.md
+++ b/docs/build/eps.md
@@ -234,7 +234,7 @@ See more information on the OpenVINO Execution Provider [here](../execution-prov
 
    Follow [documentation](https://docs.openvinotoolkit.org/2021.4/index.html) for detailed instructions.
 
-  *2021.4 is the recommended OpenVINO version. [OpenVINO 2020.3](https://docs.openvinotoolkit.org/2020.3/index.html) is minimal OpenVINO version requirement.*
+  *2021.4 is the recommended OpenVINO version. [OpenVINO 2021.2](https://docs.openvinotoolkit.org/2021.2/index.html) is minimal OpenVINO version requirement.*
   *The minimum ubuntu version to support 2021.4 is 18.04.*
 
 2. Configure the target hardware with specific follow on instructions:
diff --git a/docs/execution-providers/OpenVINO-ExecutionProvider.md b/docs/execution-providers/OpenVINO-ExecutionProvider.md
index 480898f095..cd1d6c7ab1 100644
--- a/docs/execution-providers/OpenVINO-ExecutionProvider.md
+++ b/docs/execution-providers/OpenVINO-ExecutionProvider.md
@@ -24,6 +24,7 @@ Pre-built packages and Docker images are published for  ONNX Runtime with OpenVI
 
 |ONNX Runtime|OpenVINO|Notes|
 |---|---|---|
+|1.9.0|2021.4.1|[Details](https://github.com/intel/onnxruntime/releases/tag/v3.1)|
 |1.8.1|2021.4|[Details](https://github.com/intel/onnxruntime/releases/tag/v3.0)|
 |1.8.0|2021.3|[Details](https://github.com/intel/onnxruntime/releases/tag/2021.3)|
 
@@ -33,7 +34,7 @@ For build instructions, please see the [BUILD page](../build/eps.md#openvino).
 ## Usage
 **C#**
 
-To use csharp api for openvino execution provider create a custom nuget package. Follow the instructions [here](../build/inferencing.md#build-nuget-packages) to install prerequisites for nuget creation. Once prerequisites are installed follow the instructions to [build openvino](../build/eps.md#openvino) and add an extra flag `--build_nuget` to create nuget packages. Two nuget packages will be created Microsoft.ML.OnnxRuntime.Managed and Microsoft.ML.OnnxRuntime.Openvino.
+To use csharp api for openvino execution provider create a custom nuget package. Follow the instructions [here](../build/inferencing.md#build-nuget-packages) to install prerequisites for nuget creation. Once prerequisites are installed follow the instructions to [build openvino](../build/eps.md#openvino) and add an extra flag `--build_nuget` to create nuget packages. Two nuget packages will be created Microsoft.ML.OnnxRuntime.Managed and Microsoft.ML.OnnxRuntime.Openvino. 
 
 ### Multi-threading for OpenVINO EP
 
@@ -206,7 +207,7 @@ VPUs as well as Intel<sup>®</sup> Vision accelerator Design with Intel Movidiu
 | Atanh | Yes | No | No |
 | AveragePool | Yes | Yes | Yes |
 | BatchNormalization | Yes | Yes | Yes |
-| Ceil | No | Yes | Yes |
+| Ceil | Yes | Yes | Yes |
 | Cast | Yes | Yes | Yes |
 | Clip | Yes | Yes | Yes |
 | Concat | Yes | Yes | Yes |
@@ -229,6 +230,7 @@ VPUs as well as Intel<sup>®</sup> Vision accelerator Design with Intel Movidiu
 | Floor | Yes | Yes | Yes |
 | Gather | Yes | Yes | Yes |
 | GatherElements | No | No | Yes |
+| GatherND | Yes | Yes | Yes |
 | Gemm | Yes | Yes | Yes |
 | GlobalAveragePool | Yes | Yes | Yes |
 | GlobalLpPool | Yes | Yes | No |
@@ -238,7 +240,7 @@ VPUs as well as Intel<sup>®</sup> Vision accelerator Design with Intel Movidiu
 | LeakyRelu | Yes | Yes | Yes |
 | Less | Yes | Yes | Yes |
 | Log | Yes | Yes | Yes |
-| Loop | No | No | Yes |
+| Loop | Yes | Yes | Yes |
 | LRN | Yes | Yes | Yes |
 | MatMul | Yes | Yes | Yes |
 | Max | Yes | Yes | Yes |
@@ -267,6 +269,7 @@ VPUs as well as Intel<sup>®</sup> Vision accelerator Design with Intel Movidiu
 | Reshape | Yes | Yes | Yes |
 | Resize | Yes | No | Yes |
 | RoiAlign | No | No | Yes |
+| Round | Yes | Yes | Yes |
 | Scatter | No | No | Yes |
 | Selu | Yes | Yes | No |
 | Shape | Yes | Yes | Yes |
@@ -285,7 +288,7 @@ VPUs as well as Intel<sup>®</sup> Vision accelerator Design with Intel Movidiu
 | Sum | Yes | Yes | Yes |
 | Tan | Yes | Yes | No |
 | Tanh | Yes | Yes | Yes |
-| Tile | No | No | Yes |
+| Tile | Yes | Yes | Yes |
 | TopK | Yes | Yes | Yes |
 | Transpose | Yes | Yes | Yes |
 | Unsqueeze | Yes | Yes | Yes |
@@ -340,6 +343,7 @@ Below topologies from ONNX open model zoo are fully supported on OpenVINO Execut
 | tiny_yolov3 | Yes | Yes | Yes | No* |
 | mask_rcnn | Yes | Yes | Yes | No* |
 | faster_rcnn | Yes | Yes | Yes | No* |
+| yolov4 | Yes | Yes | Yes | No* |
 | yolov5 | Yes | Yes | Yes | No* |
 
 ### Image Manipulation Networks
@@ -360,10 +364,10 @@ Below topologies from ONNX open model zoo are fully supported on OpenVINO Execut
 In order to showcase what you can do with the OpenVINO Execution Provider for ONNX Runtime, we have created a few samples that shows how you can get that performance boost you’re looking for with just one additional line of code. 
 
 ### Python API
-[Object detection with tinyYOLOv2 in Python](../../tutorials/tutorials/OpenVINO_EP_samples/tiny_yolo_v2_object_detection_python.md)
+[Object detection with tinyYOLOv2 in Python](https://github.com/microsoft/onnxruntime-inference-examples/tree/main/python/OpenVINO_EP/tiny_yolo_v2_object_detection)
 
 ### C/C++ API
-[Image classification with Squeezenet in CPP](../../tutorials/tutorials/OpenVINO_EP_samples/squeezenet_classification_cpp.md)
+[Image classification with Squeezenet in CPP](https://github.com/microsoft/onnxruntime-inference-examples/tree/main/c_cxx/OpenVINO_EP/squeezenet_classification)
 
 ### Csharp API
-[Object detection with YOLOv3 in C#](../../tutorials/tutorials/OpenVINO_EP_samples/yolov3_object_detection_csharp.md)
+[Object detection with YOLOv3 in C#](https://github.com/microsoft/onnxruntime-inference-examples/tree/main/c_sharp)