# New Release: Ultralytics v8.3.194

**URL:** <https://community.ultralytics.com/t/new-release-ultralytics-v8-3-194/1442>\
**Category:** Discussion\
**Tags:** releases, announcements, ultralytics-official\
**Created:** [September 6, 2025, 1:08pm UTC](https://community.ultralytics.com/t/new-release-ultralytics-v8-3-194/1442 "2025-09-06T13:08:14Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![glenn-jocher](https://sea1.discourse-cdn.com/flex001/user_avatar/community.ultralytics.com/glenn-jocher/32/83_2.png) [@glenn-jocher](https://community.ultralytics.com/u/glenn-jocher)\
**Post date:** [September 6, 2025, 1:08pm UTC](https://community.ultralytics.com/t/new-release-ultralytics-v8-3-194/1442/1 "2025-09-06T13:08:14Z")

</div>

# Ultralytics v8.3.194 — smoother exports, CoreML NMS, and non‑blocking telemetry 🚀

Quick summary: This release focuses on export stability and visibility, CoreML NMS inference in Python, and a telemetry refactor for clean, background event handling—plus a handful of quality‑of‑life fixes and docs updates. As always, Ultralytics YOLO defaults to YOLO11 for the best all‑around experience.

## 🌟 Summary

Ultralytics v8.3.194 delivers:

- More reliable ONNX and TensorFlow exports with improved simplification and clearer logs.
- CoreML models with embedded NMS that run directly in Python.
- A refactored, non‑blocking Events system that’s independent of Ultralytics HUB.
- Robust segmentation for dense scenes and aligned SAM‑2 examples in docs.
- Faster CI feedback for contributors.

You can review the highlights below and explore the details in the [v8.3.194 release notes](https://github.com/ultralytics/ultralytics/releases/tag/v8.3.194).

## ✨ New Features

- CoreML NMS support in Python
  - Export models with NMS embedded and run inference directly—no manual post‑processing for supported detection use cases. See the PR [Support CoreML inference with NMS embedded models](https://github.com/ultralytics/ultralytics/pull/21948) by [@Y-T-G](https://github.com/Y-T-G).
  - Example:

```bash
yolo export model=yolo11n.pt format=coreml nms=True
yolo predict model=yolo11n.mlpackage

```

## 🛠 Improvements

- Exporter dependency and logging
  - Upgraded ONNX simplifier to `onnxslim>=0.1.67` for better ONNX and TensorFlow SavedModel exports, restored `urllib3` logs for clearer troubleshooting, and kept `sentry_sdk` quiet. See [Bump onnxslim\>=0.1.67 in Exporter](https://github.com/ultralytics/ultralytics/pull/21951) by [@onuralpszr](https://github.com/onuralpszr).

- TensorFlow export stability
  - Pinned versions for export to align with `onnx2tf`: `tensorflow>=2.0.0,<=2.19.0` and `tf_keras<=2.19.0`. Details in [Pin tf\_keras\<=2.19.0](https://github.com/ultralytics/ultralytics/pull/21949) by [@Laughing-q](https://github.com/Laughing-q).

- Telemetry refactor
  - Moved anonymous Events to `ultralytics.utils.events`, running in a background thread and independent of HUB. See [Refactor Events class](https://github.com/ultralytics/ultralytics/pull/21959) by [@glenn-jocher](https://github.com/glenn-jocher).
  - If you import Events directly, update your code:

```python
from ultralytics.utils.events import events, Events

```

- Segmentation robustness
  - Prevented crashes from OpenCV’s 512‑channel `cv2.resize` limit by splitting large mask tensors. See [Handle cv2.resize 512-channel limit](https://github.com/ultralytics/ultralytics/pull/21947) by [@ShuaiLYU](https://github.com/ShuaiLYU).

- SAM‑2 API/doc consistency
  - Standardized to `source` and renamed `img` to `im` in `inference`, with updated examples. See [Fix SAM2DynamicInteractivePredictor example](https://github.com/ultralytics/ultralytics/pull/21955) by [@Y-T-G](https://github.com/Y-T-G).

## 🧪 Developer Experience

- Faster CI feedback
  - Reduced GPU CI timeout from 6 hours to 20 minutes to prevent runaway jobs. Details in [Prevent long-running billed GPU CI](https://github.com/ultralytics/ultralytics/pull/21960) by [@glenn-jocher](https://github.com/glenn-jocher).

## 📚 Docs Refresh

- New Events reference and updated queue guide
  - Explore the new [Events utils reference](https://docs.ultralytics.com/reference/utils/events/) and the refreshed [Queue Management guide](https://docs.ultralytics.com/guides/queue-management/) featuring a broader‑use tutorial video.

- Content updates
  - The documentation now includes a useful training queue walkthrough video, added in the PR [Add YouTube video to docs](https://github.com/ultralytics/ultralytics/pull/21923) by [@RizwanMunawar](https://github.com/RizwanMunawar).

## 🔍 Why it matters

- More reliable exports and fewer dependency conflicts thanks to the updated `onnxslim` and clearer logging.
- Smoother Apple workflows with CoreML NMS models that run directly in Python.
- Predictable TensorFlow export behavior via version pinning.
- Cleaner, non‑blocking telemetry that won’t slow your training or export pipelines.
- Fewer runtime errors in dense segmentation scenarios.

## 📦 How to upgrade and try it

- Upgrade:
  - `pip install -U ultralytics`

- Quick test with recommended defaults:
  - `yolo predict model=yolo11n.pt source='path/to/images'`

YOLO11 is the latest stable and recommended model for most scenarios, offering strong accuracy‑speed trade‑offs across detection, segmentation, pose, and classification.

## 🙌 PR Credits

- [Pin tf\_keras\<=2.19.0](https://github.com/ultralytics/ultralytics/pull/21949) by [@Laughing-q](https://github.com/Laughing-q)
- [Support CoreML inference with NMS embedded models](https://github.com/ultralytics/ultralytics/pull/21948) by [@Y-T-G](https://github.com/Y-T-G)
- [Split large channel masks to handle cv2.resize 512 limitations](https://github.com/ultralytics/ultralytics/pull/21947) by [@ShuaiLYU](https://github.com/ShuaiLYU)
- [Fix SAM2DynamicInteractivePredictor example in docs](https://github.com/ultralytics/ultralytics/pull/21955) by [@Y-T-G](https://github.com/Y-T-G)
- [Prevent long-running billed GPU CI](https://github.com/ultralytics/ultralytics/pull/21960) by [@glenn-jocher](https://github.com/glenn-jocher)
- [Refactor Events class](https://github.com/ultralytics/ultralytics/pull/21959) by [@glenn-jocher](https://github.com/glenn-jocher)
- [Add training queue video to docs](https://github.com/ultralytics/ultralytics/pull/21923) by [@RizwanMunawar](https://github.com/RizwanMunawar)
- [Bump onnxslim\>=0.1.67 in Exporter](https://github.com/ultralytics/ultralytics/pull/21951) by [@onuralpszr](https://github.com/onuralpszr)

Explore everything that changed in the [full changelog diff between v8.3.193 and v8.3.194](https://github.com/ultralytics/ultralytics/compare/v8.3.193...v8.3.194).

## 💬 We’d love your feedback

Please upgrade, try the new CoreML NMS workflow, and let us know how exports and telemetry behave in your environment. Share your thoughts and issues in Discussions, and feel free to open PRs with improvements. Your feedback helps the YOLO community and the Ultralytics team keep pushing forward.