MacBook Pro (13-inch, 2022)
Geekbench ML Score
9096
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | December 20 2024 07:59 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.3 (Build 24D5034f) |
| Model | MacBook Pro (13-inch, 2022) |
| Model ID | Mac14,7 |
| Motherboard | Mac14,7 |
| CPU Information | |
|---|---|
| Name | Apple M2 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M2 |
| Base Frequency | 3.44 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3347
626.2 IPS |
|
|
Image Classification (F16)
|
100% |
11405
2.13 KIPS |
|
|
Image Classification (I8)
|
99% |
12231
2.29 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1343
22.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
2007
33.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1956
32.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
22926
27.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
93424
113.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
97138
117.6 IPS |
|
|
Object Detection (F32)
|
100% |
2275
169.9 IPS |
|
|
Object Detection (F16)
|
100% |
4795
358.0 IPS |
|
|
Object Detection (I8)
|
97% |
1213
90.5 IPS |
|
|
Face Detection (F32)
|
100% |
6662
79.2 IPS |
|
|
Face Detection (F16)
|
97% |
19654
233.7 IPS |
|
|
Face Detection (I8)
|
96% |
19717
234.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
15854
122.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
48411
375.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
42859
332.4 IPS |
|
|
Style Transfer (F32)
|
100% |
40699
53.5 IPS |
|
|
Style Transfer (F16)
|
100% |
143805
189.2 IPS |
|
|
Style Transfer (I8)
|
100% |
139352
183.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6581
235.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
33215
1.19 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
34631
1.24 KIPS |
|
|
Text Classification (F32)
|
100% |
2032
2.92 KIPS |
|
|
Text Classification (F16)
|
100% |
3416
4.91 KIPS |
|
|
Text Classification (I8)
|
96% |
3388
4.87 KIPS |
|
|
Machine Translation (F32)
|
100% |
702
12.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1409
25.9 IPS |
|
|
Machine Translation (I8)
|
99% |
707
13.0 IPS |
