WebGPU性能测试
在浏览器中测量GPU的计算、内存和AI性能，并用于YOLO估算。
真实GPU基准测试
自动调整各项负载，并使用中位数测量GPU性能。
YOLO训练设置
YOLO训练设置
YOLO11 Small · 640 · 目标检测
9.4M params · 21.5B FLOPs @ 640
VRAM and speed estimates change with the selected YOLO model and image size. Dataset Images and Epochs are used to estimate training time.
请选择与实际GPU最接近的型号。
Compute
Repeated FMA shader throughput
Memory
Storage-buffer read + write throughput proxy
AI Matrix
1024×1024 tiled matrix multiplication
Production use requires HTTPS. localhost can be used for local WebGPU development.
WebGPU Benchmark
Starting the test runs real Compute / Memory / Matrix workloads on this PC's GPU.
How v2 measures
To prevent command-submit overhead from dominating fast GPUs, each workload automatically increases its repeat count. GPU timestamps are preferred when supported; otherwise v2 uses a sufficiently long calibrated wall-clock workload.
Next step
The next step is to calibrate this v2 score against measured RTX 5060 CUDA/PyTorch/YOLO results, enabling WebGPU score → YOLO recommended batch and training-speed estimates.
Important
WebGPU is not the same API or workload as PyTorch CUDA training. At this stage, WebGPU results alone are not used to claim an exact YOLO batch size or training time.
使用方法
- 输入“yolo-gpu-tester”需要的数值。
- 确认选项后运行工具。
- 查看结果并复制或保存。