MichinaMichina

Benchmarks

Test environment:

Columns in results:

These benchmarks are very simple and rough, for reference only. Result may vary on different devices, OS versions and even temperature of your computer.

Facial Recognition

Inputs:

Results:

antelopev2
  • detection 16.9 MB

    Execution ProviderOptimizationClean LoadRegular LoadInference
    Core ML (MLProgram)34 MB574 ms325 ms98 ms
    Core ML (NeuralNetwork)33.9 MB253 ms72 ms84 ms
    CPU18.5 MB52 ms42 ms249 ms
  • recognition 260.7 MB

    Execution ProviderOptimizationClean LoadRegular LoadInference
    Core ML (MLProgram)522.3 MB2.016 s969 ms466 ms
    Core ML (NeuralNetwork)522 MB4.744 s175 ms6.09 s
    CPU260.6 MB523 ms449 ms3.66 s
buffalo_l
  • detection (Same model as antelopev2 / detection)

  • recognition 174.4 MB

    Execution ProviderOptimizationClean LoadRegular LoadInference
    Core ML (MLProgram)349.3 MB1.416 s870 ms295 ms
    Core ML (NeuralNetwork)349.1 MB2.287 s122 ms4.33 s
    CPU174.3 MB287 ms259 ms1.95 s
buffalo_m
  • detection 3.3 MB

    Execution ProviderOptimizationClean LoadRegular LoadInference
    Core ML (MLProgram)6.7 MB510 ms316 ms32 ms
    Core ML (NeuralNetwork)6.7 MB171 ms78 ms45 ms
    CPU3.8 MB27 ms27 ms88 ms
  • recognition (Same model as buffalo_l / recognition)

buffalo_s
  • detection 2.5 MB

    Execution ProviderOptimizationClean LoadRegular LoadInference
    Core ML (MLProgram)5.2 MB519 ms333 ms61 ms
    Core ML (NeuralNetwork)5.1 MB171 ms77 ms31 ms
    CPU2.8 MB25 ms21 ms32 ms
  • recognition 13.6 MB

    Execution ProviderOptimizationClean LoadRegular LoadInference
    Core ML (MLProgram)27.4 MB356 ms229 ms348 ms
    Core ML (NeuralNetwork)27.3 MB566 ms44 ms29 ms
    CPU13.6 MB49 ms42 ms141 ms
apple-vision

The numbers of detected face are significantly less than all other models.

  • detection Apple's Vision Framework
    Execution ProviderOptimizationClean LoadRegular LoadInference
    ----208 ms

Smart Search (CLIP)

Inputs:

Results:

ViT-SO400M-16-SigLIP2-384__webli
  • visual 1.71 GB

    Execution ProviderOptimizationClean LoadRegular LoadInference
    Core ML (MLProgram)8.28 GB1393 s201 s287 ms
    Core ML (NeuralNetwork)3.42 GB17.32 s2.637 s599 ms
    CPU1.71 GB3.674 s2.846 s2.96 s
  • textual 2.87 GB

    Execution ProviderOptimizationClean LoadRegular LoadInference
    Core ML (MLProgram)9.95 GB889 s263 s159 ms
    Core ML (NeuralNetwork)5.67 GB28.136 s3.218 s273 ms
    CPU334 KB4.878 s4.695 s305 ms

Character Recognition (OCR)

Results:

PP-OCRv5_server

Unable to load in MLProgram format, error:

Failed to parse the model specification. Error: Unable to parse ML Program: in operation MaxPool.0: ceil_mode must be False when pad_type is equal to same

  • detection 88.1 MB

    Execution ProviderOptimizationClean LoadRegular LoadInference
    Core ML (MLProgram)----
    Core ML (NeuralNetwork)175.4 MB1.318 s114 ms655 ms
    CPU87.8 MB136 ms109 ms3.13 s
  • recognition 84.6 MB

    Execution ProviderOptimizationClean LoadRegular LoadInference
    Core ML (MLProgram)----
    Core ML (NeuralNetwork)149 MB941 ms171 ms2.56 s
    CPU84.3 MB165 ms136 ms5.13 s
PP-OCRv5_mobile

The outputs from Core ML (NeuralNetwork) are likely incorrect.

  • detection 4.8 MB

    Execution ProviderOptimizationClean LoadRegular LoadInference
    Core ML (MLProgram)9.8 MB4.116 s2.733 s699 ms
    Core ML (NeuralNetwork)9.7 MB590 ms161 ms-
    CPU5 MB46 ms49 ms356 ms
  • recognition 16.6 MB

    Execution ProviderOptimizationClean LoadRegular LoadInference
    Core ML (MLProgram)33.3 MB5.245 s3.474 s43.58 s
    Core ML (NeuralNetwork)13.8 MB566 ms211 ms-
    CPU16.7 MB85 ms79 ms1.06 s