MacBook Pro (16-inch Late 2019)
Geekbench ML Score
735
Core ML CPU Inference Score
Geekbench ML 0.6.0 for macOS AVX2
Result Information
| Upload Date | January 10 2024 10:50 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.2.1 (Build 23C71) |
| Model | MacBook Pro (16-inch Late 2019) |
| Model ID | MacBookPro16,1 |
| Motherboard | Apple Inc. Mac-E1008331FDC96864 MacBookPro16,1 |
| CPU Information | |
|---|---|
| Name | Intel Core i9-9880H |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 13 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 32.0 KB x 8 |
| L2 Cache | 256 KB x 8 |
| L3 Cache | 16.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Transfer Rate | 2667 MT/s |
| Type | DDR4 |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
425
79.5 IPS |
|
|
Image Classification (F16)
|
100% |
306
57.2 IPS |
|
|
Image Classification (I8)
|
99% |
313
58.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
216
3.61 IPS |
|
|
Image Segmentation (F16)
|
100% |
210
3.51 IPS |
|
|
Image Segmentation (I8)
|
100% |
211
3.52 IPS |
|
|
Pose Estimation (F32)
|
100% |
2112
2.56 IPS |
|
|
Pose Estimation (F16)
|
100% |
2124
2.57 IPS |
|
|
Pose Estimation (I8)
|
100% |
2003
2.43 IPS |
|
|
Object Detection (F32)
|
100% |
445
33.2 IPS |
|
|
Object Detection (F16)
|
100% |
341
25.4 IPS |
|
|
Object Detection (I8)
|
97% |
445
33.2 IPS |
|
|
Face Detection (F32)
|
100% |
813
9.67 IPS |
|
|
Face Detection (F16)
|
100% |
824
9.80 IPS |
|
|
Face Detection (I8)
|
99% |
804
9.55 IPS |
|
|
Depth Estimation (F32)
|
100% |
1133
8.79 IPS |
|
|
Depth Estimation (F16)
|
100% |
977
7.57 IPS |
|
|
Depth Estimation (I8)
|
99% |
978
7.58 IPS |
|
|
Style Transfer (F32)
|
100% |
4239
5.58 IPS |
|
|
Style Transfer (F16)
|
100% |
3692
4.86 IPS |
|
|
Style Transfer (I8)
|
100% |
3732
4.91 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1868
66.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1832
65.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1847
66.0 IPS |
|
|
Text Classification (F32)
|
100% |
495
711.3 IPS |
|
|
Text Classification (F16)
|
100% |
354
509.3 IPS |
|
|
Text Classification (I8)
|
96% |
358
514.4 IPS |
|
|
Machine Translation (F32)
|
100% |
332
6.11 IPS |
|
|
Machine Translation (F16)
|
100% |
286
5.26 IPS |
|
|
Machine Translation (I8)
|
99% |
334
6.14 IPS |
