ultralytics 8.4.72

v8.4.72 - Fix TensorRT INT8 export crash on RTX cards exposing the NvTensorRTRTX EP (#24876)

on Python PyPI

🌟 Summary

v8.4.72 is a small but important stability release that mainly fixes a TensorRT INT8 export crash on some RTX GPUs 🚀, while also improving export environment reliability and cleaning up docs/CI.

📊 Key Changes

• Fixed TensorRT INT8 export crashes on certain RTX cards 🔧

  • The most important change in this release is from PR #24876 by @glenn-jocher.
  • Exporting models with format="engine", int8=True could fail on some RTX GPUs, including cases where ONNX Runtime exposed both TensorRT execution providers.
  • Ultralytics changed the INT8 calibration step to use CUDA with CPU fallback instead of triggering conflicting TensorRT provider combinations.

• Improved TensorRT/ONNX export image compatibility for CUDA 12 🐳

  • PR #24877 pins onnxruntime-gpu to below 1.27.0 in the export Docker image.
  • This avoids breakage caused by newer ONNX Runtime GPU builds that now expect CUDA 13, while the export image still uses CUDA 12.8.

• GitHub Actions checkout updated from v6 to v7 ⚙️

  • PR #24873 refreshes CI workflows to a newer actions/checkout version.
  • This is a maintenance update for the project’s automation pipeline.

• Documentation updates and cleanup 📚

  • PR #24863 refreshes the Queue Management guide with a newer YOLO26 video and updated wording.
  • PR #24875 simplifies the Triton C++ example README by removing extra contributor footer content.
  • PR #24851 adds clearer page titles for account settings and YOLO configuration docs, helping site clarity and SEO.

🎯 Purpose & Impact

• More reliable INT8 TensorRT exports on RTX hardware 💡

  • Users exporting optimized TensorRT engines should see fewer failures on affected NVIDIA RTX systems.
  • This is especially helpful for developers deploying compact, fast INT8 inference pipelines.

• Better support for modern RTX environments 🖥️

  • The fix avoids a low-level ONNX Runtime provider conflict that was causing exports to crash before the model was even fully built.
  • In simple terms: INT8 export now works more reliably on hardware that previously broke unexpectedly.

• Safer Docker-based export workflows 🛡️

  • Pinning onnxruntime-gpu prevents version mismatches that could break ONNX inference and export tests inside CUDA 12 environments.
  • This should make CI and container-based deployment setups more predictable.

• No major model architecture changes 📌

  • This release does not introduce a new model or training feature.
  • The focus is on export stability, environment compatibility, and documentation polish.

• Practical benefit for users ✅

  • If you use Ultralytics for training and then export to TensorRT INT8 for production, this release is worth adopting.
  • If you mainly use standard training or FP16 export, the impact is smaller but still positive thanks to general reliability improvements.

What's Changed

• Add https://youtu.be/TEVPiGCxB0o to docs by @RizwanMunawar in #24863
• docs: small cleanup triton contributions by @onuralpszr in #24875
• Pin onnxruntime-gpu<1.27.0 for CUDA 12 export image by @glenn-jocher in #24877
• Bump actions/checkout from v6 to v7 in /.github/workflows by @UltralyticsAssistant in #24873
• Fix duplicate title tags on Spanish account settings and YOLO config pages by @miles-deans-ultralytics in #24851
• Fix TensorRT INT8 export crash on RTX cards exposing the NvTensorRTRTX EP by @glenn-jocher in #24876

Full Changelog: v8.4.71...v8.4.72