docs: 📝 link updates and fix broken links for download models

README.md

@@ -29,7 +29,7 @@ model-index:
 ---
 <div align="center">
   <p>
-    <a href="https://www.ultralytics.com/blog/ultralytics-yolo26-the-new-standard-for-edge-first-vision-ai" target="_blank">
+    <a href="http://platform.ultralytics.com/" target="_blank">
       <img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/banner-yolov8.png" alt="Ultralytics YOLO banner"></a>
   </p>
   <p style="margin: 3px 0;">
@@ -150,7 +150,7 @@ Discover more examples in the YOLO [Python Docs](https://docs.ultralytics.com/us
 
 ## <div align="center">✨ Models</div>
 
-Ultralytics supports a wide range of YOLO models, from early versions like [YOLOv3](https://docs.ultralytics.com/models/yolov3/) to the latest [YOLO26](https://docs.ultralytics.com/models/yolo26/). The tables below showcase YOLO26 models pretrained on the [COCO](https://docs.ultralytics.com/datasets/detect/coco/) dataset for [Detection](https://docs.ultralytics.com/tasks/detect/), [Segmentation](https://docs.ultralytics.com/tasks/segment/), and [Pose Estimation](https://docs.ultralytics.com/tasks/pose/). Additionally, [Classification](https://docs.ultralytics.com/tasks/classify/) models pretrained on the [ImageNet](https://docs.ultralytics.com/datasets/classify/imagenet/) dataset are available. [Tracking](https://docs.ultralytics.com/modes/track/) mode is compatible with all Detection, Segmentation, and Pose models. All [Models](https://docs.ultralytics.com/models/) are automatically downloaded from the latest Ultralytics [release](https://github.com/ultralytics/assets/releases) upon first use.
+Ultralytics supports a wide range of YOLO models, from early versions like [YOLOv3](https://docs.ultralytics.com/models/yolov3/) to the latest [Ultralytics YOLO26](https://platform.ultralytics.com/ultralytics/yolo26). The tables below showcase Ultralytics YOLO26 models pretrained on the [COCO](https://docs.ultralytics.com/datasets/detect/coco/) dataset for [Detection](https://docs.ultralytics.com/tasks/detect/), [Segmentation](https://docs.ultralytics.com/tasks/segment/), and [Pose Estimation](https://docs.ultralytics.com/tasks/pose/). Additionally, [Classification](https://docs.ultralytics.com/tasks/classify/) models pretrained on the [ImageNet](https://docs.ultralytics.com/datasets/classify/imagenet/) dataset are available. [Tracking](https://docs.ultralytics.com/modes/track/) mode is compatible with all Detection, Segmentation, and Pose models. All [Models](https://docs.ultralytics.com/models/) are automatically downloaded from the latest Ultralytics [release](https://github.com/ultralytics/assets/releases) upon first use.
 
 <img width="1024" src="https://raw.githubusercontent.com/ultralytics/assets/main/im/banner-tasks.png" alt="Ultralytics YOLO supported tasks">
 
@@ -160,11 +160,11 @@ Explore the [Detection Docs](https://docs.ultralytics.com/tasks/detect/) for usa
 
 | Model | size<br><sup>(pixels) | mAP<sup>val<br>50-95 | mAP<sup>val<br>50-95(e2e) | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>T4 TensorRT10<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |
 | ------------------------------------------------------------------------------------ | --------------------- | -------------------- | ------------------------- | ------------------------------ | ----------------------------------- | ------------------ | ----------------- |
-| [YOLO26n](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26n.pt) | 640 | 40.9 | 40.1 | 38.9 ± 0.7 | 1.7 ± 0.0 | 2.4 | 5.4 |
-| [YOLO26s](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26s.pt) | 640 | 48.6 | 47.8 | 87.2 ± 0.9 | 2.5 ± 0.0 | 9.5 | 20.7 |
-| [YOLO26m](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26m.pt) | 640 | 53.1 | 52.5 | 220.0 ± 1.4 | 4.7 ± 0.1 | 20.4 | 68.2 |
-| [YOLO26l](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26l.pt) | 640 | 55.0 | 54.4 | 286.2 ± 2.0 | 6.2 ± 0.2 | 24.8 | 86.4 |
-| [YOLO26x](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26x.pt) | 640 | 57.5 | 56.9 | 525.8 ± 4.0 | 11.8 ± 0.2 | 55.7 | 193.9 |
+| [YOLO26n](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26n.pt) | 640 | 40.9 | 40.1 | 38.9 ± 0.7 | 1.7 ± 0.0 | 2.4 | 5.4 |
+| [YOLO26s](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26s.pt) | 640 | 48.6 | 47.8 | 87.2 ± 0.9 | 2.5 ± 0.0 | 9.5 | 20.7 |
+| [YOLO26m](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26m.pt) | 640 | 53.1 | 52.5 | 220.0 ± 1.4 | 4.7 ± 0.1 | 20.4 | 68.2 |
+| [YOLO26l](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26l.pt) | 640 | 55.0 | 54.4 | 286.2 ± 2.0 | 6.2 ± 0.2 | 24.8 | 86.4 |
+| [YOLO26x](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26x.pt) | 640 | 57.5 | 56.9 | 525.8 ± 4.0 | 11.8 ± 0.2 | 55.7 | 193.9 |
 
 - **mAP<sup>val</sup>** values refer to single-model single-scale performance on the [COCO val2017](https://cocodataset.org/) dataset. See [YOLO Performance Metrics](https://docs.ultralytics.com/guides/yolo-performance-metrics/) for details. <br>Reproduce with `yolo val detect data=coco.yaml device=0`
 - **Speed** metrics are averaged over COCO val images using an [Amazon EC2 P4d](https://aws.amazon.com/ec2/instance-types/p4/) instance. CPU speeds measured with [ONNX](https://onnx.ai/) export. GPU speeds measured with [TensorRT](https://developer.nvidia.com/tensorrt) export. <br>Reproduce with `yolo val detect data=coco.yaml batch=1 device=0|cpu`
@@ -177,11 +177,11 @@ Refer to the [Segmentation Docs](https://docs.ultralytics.com/tasks/segment/) fo
 
 | Model | size<br><sup>(pixels) | mAP<sup>box<br>50-95(e2e) | mAP<sup>mask<br>50-95(e2e) | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>T4 TensorRT10<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |
 | -------------------------------------------------------------------------------------------- | --------------------- | ------------------------- | -------------------------- | ------------------------------ | ----------------------------------- | ------------------ | ----------------- |
-| [YOLO26n-seg](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26n-seg.pt) | 640 | 39.6 | 33.9 | 53.3 ± 0.5 | 2.1 ± 0.0 | 2.7 | 9.1 |
-| [YOLO26s-seg](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26s-seg.pt) | 640 | 47.3 | 40.0 | 118.4 ± 0.9 | 3.3 ± 0.0 | 10.4 | 34.2 |
-| [YOLO26m-seg](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26m-seg.pt) | 640 | 52.5 | 44.1 | 328.2 ± 2.4 | 6.7 ± 0.1 | 23.6 | 121.5 |
-| [YOLO26l-seg](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26l-seg.pt) | 640 | 54.4 | 45.5 | 387.0 ± 3.7 | 8.0 ± 0.1 | 28.0 | 139.8 |
-| [YOLO26x-seg](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26x-seg.pt) | 640 | 56.5 | 47.0 | 787.0 ± 6.8 | 16.4 ± 0.1 | 62.8 | 313.5 |
+| [YOLO26n-seg](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26n-seg.pt) | 640 | 39.6 | 33.9 | 53.3 ± 0.5 | 2.1 ± 0.0 | 2.7 | 9.1 |
+| [YOLO26s-seg](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26s-seg.pt) | 640 | 47.3 | 40.0 | 118.4 ± 0.9 | 3.3 ± 0.0 | 10.4 | 34.2 |
+| [YOLO26m-seg](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26m-seg.pt) | 640 | 52.5 | 44.1 | 328.2 ± 2.4 | 6.7 ± 0.1 | 23.6 | 121.5 |
+| [YOLO26l-seg](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26l-seg.pt) | 640 | 54.4 | 45.5 | 387.0 ± 3.7 | 8.0 ± 0.1 | 28.0 | 139.8 |
+| [YOLO26x-seg](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26x-seg.pt) | 640 | 56.5 | 47.0 | 787.0 ± 6.8 | 16.4 ± 0.1 | 62.8 | 313.5 |
 
 - **mAP<sup>val</sup>** values are for single-model single-scale on the [COCO val2017](https://cocodataset.org/) dataset. See [YOLO Performance Metrics](https://docs.ultralytics.com/guides/yolo-performance-metrics/) for details. <br>Reproduce with `yolo val segment data=coco.yaml device=0`
 - **Speed** metrics are averaged over COCO val images using an [Amazon EC2 P4d](https://aws.amazon.com/ec2/instance-types/p4/) instance. CPU speeds measured with [ONNX](https://onnx.ai/) export. GPU speeds measured with [TensorRT](https://developer.nvidia.com/tensorrt) export. <br>Reproduce with `yolo val segment data=coco.yaml batch=1 device=0|cpu`
@@ -194,11 +194,11 @@ Consult the [Classification Docs](https://docs.ultralytics.com/tasks/classify/)
 
 | Model | size<br><sup>(pixels) | acc<br><sup>top1 | acc<br><sup>top5 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>T4 TensorRT10<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) at 224 |
 | -------------------------------------------------------------------------------------------- | --------------------- | ---------------- | ---------------- | ------------------------------ | ----------------------------------- | ------------------ | ------------------------ |
-| [YOLO26n-cls](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26n-cls.pt) | 224 | 71.4 | 90.1 | 5.0 ± 0.3 | 1.1 ± 0.0 | 2.8 | 0.5 |
-| [YOLO26s-cls](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26s-cls.pt) | 224 | 76.0 | 92.9 | 7.9 ± 0.2 | 1.3 ± 0.0 | 6.7 | 1.6 |
-| [YOLO26m-cls](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26m-cls.pt) | 224 | 78.1 | 94.2 | 17.2 ± 0.4 | 2.0 ± 0.0 | 11.6 | 4.9 |
-| [YOLO26l-cls](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26l-cls.pt) | 224 | 79.0 | 94.6 | 23.2 ± 0.3 | 2.8 ± 0.0 | 14.1 | 6.2 |
-| [YOLO26x-cls](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26x-cls.pt) | 224 | 79.9 | 95.0 | 41.4 ± 0.9 | 3.8 ± 0.0 | 29.6 | 13.6 |
+| [YOLO26n-cls](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26n-cls.pt) | 224 | 71.4 | 90.1 | 5.0 ± 0.3 | 1.1 ± 0.0 | 2.8 | 0.5 |
+| [YOLO26s-cls](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26s-cls.pt) | 224 | 76.0 | 92.9 | 7.9 ± 0.2 | 1.3 ± 0.0 | 6.7 | 1.6 |
+| [YOLO26m-cls](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26m-cls.pt) | 224 | 78.1 | 94.2 | 17.2 ± 0.4 | 2.0 ± 0.0 | 11.6 | 4.9 |
+| [YOLO26l-cls](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26l-cls.pt) | 224 | 79.0 | 94.6 | 23.2 ± 0.3 | 2.8 ± 0.0 | 14.1 | 6.2 |
+| [YOLO26x-cls](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26x-cls.pt) | 224 | 79.9 | 95.0 | 41.4 ± 0.9 | 3.8 ± 0.0 | 29.6 | 13.6 |
 
 - **acc** values represent model accuracy on the [ImageNet](https://www.image-net.org/) dataset validation set. <br>Reproduce with `yolo val classify data=path/to/ImageNet device=0`
 - **Speed** metrics are averaged over ImageNet val images using an [Amazon EC2 P4d](https://aws.amazon.com/ec2/instance-types/p4/) instance. CPU speeds measured with [ONNX](https://onnx.ai/) export. GPU speeds measured with [TensorRT](https://developer.nvidia.com/tensorrt) export. <br>Reproduce with `yolo val classify data=path/to/ImageNet batch=1 device=0|cpu`
@@ -211,11 +211,11 @@ See the [Pose Estimation Docs](https://docs.ultralytics.com/tasks/pose/) for usa
 
 | Model | size<br><sup>(pixels) | mAP<sup>pose<br>50-95(e2e) | mAP<sup>pose<br>50(e2e) | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>T4 TensorRT10<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |
 | ---------------------------------------------------------------------------------------------- | --------------------- | -------------------------- | ----------------------- | ------------------------------ | ----------------------------------- | ------------------ | ----------------- |
-| [YOLO26n-pose](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26n-pose.pt) | 640 | 57.2 | 83.3 | 40.3 ± 0.5 | 1.8 ± 0.0 | 2.9 | 7.5 |
-| [YOLO26s-pose](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26s-pose.pt) | 640 | 63.0 | 86.6 | 85.3 ± 0.9 | 2.7 ± 0.0 | 10.4 | 23.9 |
-| [YOLO26m-pose](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26m-pose.pt) | 640 | 68.8 | 89.6 | 218.0 ± 1.5 | 5.0 ± 0.1 | 21.5 | 73.1 |
-| [YOLO26l-pose](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26l-pose.pt) | 640 | 70.4 | 90.5 | 275.4 ± 2.4 | 6.5 ± 0.1 | 25.9 | 91.3 |
-| [YOLO26x-pose](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26x-pose.pt) | 640 | 71.6 | 91.6 | 565.4 ± 3.0 | 12.2 ± 0.2 | 57.6 | 201.7 |
+| [YOLO26n-pose](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26n-pose.pt) | 640 | 57.2 | 83.3 | 40.3 ± 0.5 | 1.8 ± 0.0 | 2.9 | 7.5 |
+| [YOLO26s-pose](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26s-pose.pt) | 640 | 63.0 | 86.6 | 85.3 ± 0.9 | 2.7 ± 0.0 | 10.4 | 23.9 |
+| [YOLO26m-pose](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26m-pose.pt) | 640 | 68.8 | 89.6 | 218.0 ± 1.5 | 5.0 ± 0.1 | 21.5 | 73.1 |
+| [YOLO26l-pose](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26l-pose.pt) | 640 | 70.4 | 90.5 | 275.4 ± 2.4 | 6.5 ± 0.1 | 25.9 | 91.3 |
+| [YOLO26x-pose](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26x-pose.pt) | 640 | 71.6 | 91.6 | 565.4 ± 3.0 | 12.2 ± 0.2 | 57.6 | 201.7 |
 
 - **mAP<sup>val</sup>** values are for single-model single-scale on the [COCO Keypoints val2017](https://docs.ultralytics.com/datasets/pose/coco/) dataset. See [YOLO Performance Metrics](https://docs.ultralytics.com/guides/yolo-performance-metrics/) for details. <br>Reproduce with `yolo val pose data=coco-pose.yaml device=0`
 - **Speed** metrics are averaged over COCO val images using an [Amazon EC2 P4d](https://aws.amazon.com/ec2/instance-types/p4/) instance. CPU speeds measured with [ONNX](https://onnx.ai/) export. GPU speeds measured with [TensorRT](https://developer.nvidia.com/tensorrt) export. <br>Reproduce with `yolo val pose data=coco-pose.yaml batch=1 device=0|cpu`
@@ -228,11 +228,11 @@ Check the [OBB Docs](https://docs.ultralytics.com/tasks/obb/) for usage examples
 
 | Model | size<br><sup>(pixels) | mAP<sup>test<br>50-95(e2e) | mAP<sup>test<br>50(e2e) | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>T4 TensorRT10<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |
 | -------------------------------------------------------------------------------------------- | --------------------- | -------------------------- | ----------------------- | ------------------------------ | ----------------------------------- | ------------------ | ----------------- |
-| [YOLO26n-obb](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26n-obb.pt) | 1024 | 52.4 | 78.9 | 97.7 ± 0.9 | 2.8 ± 0.0 | 2.5 | 14.0 |
-| [YOLO26s-obb](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26s-obb.pt) | 1024 | 54.8 | 80.9 | 218.0 ± 1.4 | 4.9 ± 0.1 | 9.8 | 55.1 |
-| [YOLO26m-obb](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26m-obb.pt) | 1024 | 55.3 | 81.0 | 579.2 ± 3.8 | 10.2 ± 0.3 | 21.2 | 183.3 |
-| [YOLO26l-obb](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26l-obb.pt) | 1024 | 56.2 | 81.6 | 735.6 ± 3.1 | 13.0 ± 0.2 | 25.6 | 230.0 |
-| [YOLO26x-obb](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo26x-obb.pt) | 1024 | 56.7 | 81.7 | 1485.7 ± 11.5 | 30.5 ± 0.9 | 57.6 | 516.5 |
+| [YOLO26n-obb](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26n-obb.pt) | 1024 | 52.4 | 78.9 | 97.7 ± 0.9 | 2.8 ± 0.0 | 2.5 | 14.0 |
+| [YOLO26s-obb](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26s-obb.pt) | 1024 | 54.8 | 80.9 | 218.0 ± 1.4 | 4.9 ± 0.1 | 9.8 | 55.1 |
+| [YOLO26m-obb](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26m-obb.pt) | 1024 | 55.3 | 81.0 | 579.2 ± 3.8 | 10.2 ± 0.3 | 21.2 | 183.3 |
+| [YOLO26l-obb](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26l-obb.pt) | 1024 | 56.2 | 81.6 | 735.6 ± 3.1 | 13.0 ± 0.2 | 25.6 | 230.0 |
+| [YOLO26x-obb](https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26x-obb.pt) | 1024 | 56.7 | 81.7 | 1485.7 ± 11.5 | 30.5 ± 0.9 | 57.6 | 516.5 |
 
 - **mAP<sup>test</sup>** values are for single-model multiscale performance on the [DOTAv1 test set](https://captain-whu.github.io/DOTA/dataset.html). <br>Reproduce by `yolo val obb data=DOTAv1.yaml device=0 split=test` and submit merged results to the [DOTA evaluation server](https://captain-whu.github.io/DOTA/evaluation.html).
 - **Speed** metrics are averaged over [DOTAv1 val images](https://docs.ultralytics.com/datasets/obb/dota-v2/#dota-v10) using an [Amazon EC2 P4d](https://aws.amazon.com/ec2/instance-types/p4/) instance. CPU speeds measured with [ONNX](https://onnx.ai/) export. GPU speeds measured with [TensorRT](https://developer.nvidia.com/tensorrt) export. <br>Reproduce by `yolo val obb data=DOTAv1.yaml batch=1 device=0|cpu`