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Intel Core Ultra benchmarks (#15895)

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Co-authored-by: Ultralytics Assistant <135830346+UltralyticsAssistant@users.noreply.github.com>
Co-authored-by: Burhan <62214284+Burhan-Q@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Francesco Mattioli 2 months ago committed by GitHub
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      docs/en/integrations/openvino.md

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@ -251,6 +251,92 @@ Benchmarks below run on 13th Gen Intel® Core® i7-13700H CPU at FP32 precision.
| YOLOv8x | ONNX | ✅ | 260.4 | 0.6650 | 526.66 |
| YOLOv8x | OpenVINO | ✅ | 260.6 | 0.6619 | 158.73 |
### Intel Ultra 7 155H Meteor Lake CPU
The Intel® Ultra™ 7 155H represents a new benchmark in high-performance computing, designed to cater to the most demanding users, from gamers to content creators. The Ultra™ 7 155H is not just a CPU; it integrates a powerful GPU and an advanced NPU (Neural Processing Unit) within a single chip, offering a comprehensive solution for diverse computing needs.
This hybrid architecture allows the Ultra™ 7 155H to excel in both traditional CPU tasks and GPU-accelerated workloads, while the NPU enhances AI-driven processes, enabling faster and more efficient machine learning operations. This makes the Ultra™ 7 155H a versatile choice for applications requiring high-performance graphics, complex computations, and AI inference.
The Ultra™ 7 series includes multiple models, each offering different levels of performance, with the 'H' designation indicating a high-power variant suitable for laptops and compact devices. Early benchmarks have highlighted the exceptional performance of the Ultra™ 7 155H, particularly in multitasking environments, where the combined power of the CPU, GPU, and NPU leads to remarkable efficiency and speed.
As part of Intel's commitment to cutting-edge technology, the Ultra™ 7 155H is designed to meet the needs of future computing, with more models expected to be released. The availability of the Ultra™ 7 155H varies by region, and it continues to receive praise for its integration of three powerful processing units in a single chip, setting new standards in computing performance.
Benchmarks below run on Intel® Ultra™ 7 155H at FP32 and INT8 precision.
!!! tip "Benchmarks"
=== "Integrated Intel® Arc™ GPU"
| Model | Format | Precision | Status | Size (MB) | metrics/mAP50-95(B) | Inference time (ms/im) |
| ------- | ----------- | --------- | ------ | --------- | ------------------- | ---------------------- |
| YOLOv8n | PyTorch | FP32 | ✅ | 6.2 | 0.6381 | 35.95 |
| YOLOv8n | OpenVINO | FP32 | ✅ | 12.3 | 0.6117 | 8.32 |
| YOLOv8n | OpenVINO | INT8 | ✅ | 3.6 | 0.5791 | 9.88 |
| YOLOv8s | PyTorch | FP32 | ✅ | 21.5 | 0.6967 | 79.72 |
| YOLOv8s | OpenVINO | FP32 | ✅ | 42.9 | 0.7136 | 13.37 |
| YOLOv8s | OpenVINO | INT8 | ✅ | 11.2 | 0.7086 | 9.96 |
| YOLOv8m | PyTorch | FP32 | ✅ | 49.7 | 0.737 | 202.05 |
| YOLOv8m | OpenVINO | FP32 | ✅ | 99.1 | 0.7331 | 28.07 |
| YOLOv8m | OpenVINO | INT8 | ✅ | 25.5 | 0.7259 | 21.11 |
| YOLOv8l | PyTorch | FP32 | ✅ | 83.7 | 0.7769 | 393.37 |
| YOLOv8l | OpenVINO | FP32 | ✅ | 167.0 | 0.0 | 52.73 |
| YOLOv8l | OpenVINO | INT8 | ✅ | 42.6 | 0.7861 | 28.11 |
| YOLOv8x | PyTorch | FP32 | ✅ | 130.5 | 0.7759 | 610.71 |
| YOLOv8x | OpenVINO | FP32 | ✅ | 260.6 | 0.748 | 73.51 |
| YOLOv8x | OpenVINO | INT8 | ✅ | 66.0 | 0.8085 | 51.71 |
<div align="center">
<img width="800" src="https://github.com/ultralytics/docs/releases/download/0/intel-ultra-gpu.avif" alt="Intel Core Ultra GPU benchmarks">
</div>
=== "Intel® Meteor Lake CPU"
| Model | Format | Precision | Status | Size (MB) | metrics/mAP50-95(B) | Inference time (ms/im) |
| ------- | ----------- | --------- | ------ | --------- | ------------------- | ---------------------- |
| YOLOv8n | PyTorch | FP32 | ✅ | 6.2 | 0.6381 | 34.69 |
| YOLOv8n | OpenVINO | FP32 | ✅ | 12.3 | 0.6092 | 39.06 |
| YOLOv8n | OpenVINO | INT8 | ✅ | 3.6 | 0.5968 | 18.37 |
| YOLOv8s | PyTorch | FP32 | ✅ | 21.5 | 0.6967 | 79.9 |
| YOLOv8s | OpenVINO | FP32 | ✅ | 42.9 | 0.7136 | 82.6 |
| YOLOv8s | OpenVINO | INT8 | ✅ | 11.2 | 0.7083 | 29.51 |
| YOLOv8m | PyTorch | FP32 | ✅ | 49.7 | 0.737 | 202.43 |
| YOLOv8m | OpenVINO | FP32 | ✅ | 99.1 | 0.728 | 181.27 |
| YOLOv8m | OpenVINO | INT8 | ✅ | 25.5 | 0.7285 | 51.25 |
| YOLOv8l | PyTorch | FP32 | ✅ | 83.7 | 0.7769 | 385.87 |
| YOLOv8l | OpenVINO | FP32 | ✅ | 167.0 | 0.7551 | 347.75 |
| YOLOv8l | OpenVINO | INT8 | ✅ | 42.6 | 0.7675 | 91.66 |
| YOLOv8x | PyTorch | FP32 | ✅ | 130.5 | 0.7759 | 603.63 |
| YOLOv8x | OpenVINO | FP32 | ✅ | 260.6 | 0.7479 | 516.39 |
| YOLOv8x | OpenVINO | INT8 | ✅ | 66.0 | 0.8119 | 142.42 |
<div align="center">
<img width="800" src="https://github.com/ultralytics/docs/releases/download/0/intel-ultra-cpu.avif" alt="Intel Core Ultra CPU benchmarks">
</div>
=== "Integrated Intel® AI Boost NPU"
| Model | Format | Precision | Status | Size (MB) | metrics/mAP50-95(B) | Inference time (ms/im) |
| ------- | ----------- | --------- | ------ | --------- | ------------------- | ---------------------- |
| YOLOv8n | PyTorch | FP32 | ✅ | 6.2 | 0.6381 | 36.98 |
| YOLOv8n | OpenVINO | FP32 | ✅ | 12.3 | 0.6103 | 16.68 |
| YOLOv8n | OpenVINO | INT8 | ✅ | 3.6 | 0.5941 | 14.6 |
| YOLOv8s | PyTorch | FP32 | ✅ | 21.5 | 0.6967 | 79.76 |
| YOLOv8s | OpenVINO | FP32 | ✅ | 42.9 | 0.7144 | 32.89 |
| YOLOv8s | OpenVINO | INT8 | ✅ | 11.2 | 0.7062 | 26.13 |
| YOLOv8m | PyTorch | FP32 | ✅ | 49.7 | 0.737 | 201.44 |
| YOLOv8m | OpenVINO | FP32 | ✅ | 99.1 | 0.7284 | 54.4 |
| YOLOv8m | OpenVINO | INT8 | ✅ | 25.5 | 0.7268 | 30.76 |
| YOLOv8l | PyTorch | FP32 | ✅ | 83.7 | 0.7769 | 385.46 |
| YOLOv8l | OpenVINO | FP32 | ✅ | 167.0 | 0.7539 | 80.1 |
| YOLOv8l | OpenVINO | INT8 | ✅ | 42.6 | 0.7508 | 52.25 |
| YOLOv8x | PyTorch | FP32 | ✅ | 130.5 | 0.7759 | 609.4 |
| YOLOv8x | OpenVINO | FP32 | ✅ | 260.6 | 0.7637 | 104.79 |
| YOLOv8x | OpenVINO | INT8 | ✅ | 66.0 | 0.8077 | 64.96 |
<div align="center">
<img width="800" src="https://github.com/ultralytics/docs/releases/download/0/intel-ultra-npu.avif" alt="Intel Core Ultra NPU benchmarks">
</div>
## Reproduce Our Results
To reproduce the Ultralytics benchmarks above on all export [formats](../modes/export.md) run this code:

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