MacBook Pro (13-inch, 2022)
Geekbench ML Score
9547
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | January 06 2025 08:57 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 | 3.18 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% |
3216
601.8 IPS |
|
|
Image Classification (F16)
|
100% |
9234
1.73 KIPS |
|
|
Image Classification (I8)
|
99% |
11094
2.08 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1396
23.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1950
32.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
1987
33.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
23219
28.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
94438
114.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
96636
117.0 IPS |
|
|
Object Detection (F32)
|
100% |
2540
189.7 IPS |
|
|
Object Detection (F16)
|
100% |
4743
354.1 IPS |
|
|
Object Detection (I8)
|
97% |
2594
193.7 IPS |
|
|
Face Detection (F32)
|
100% |
9075
107.9 IPS |
|
|
Face Detection (F16)
|
97% |
19838
235.9 IPS |
|
|
Face Detection (I8)
|
96% |
19606
233.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
15617
121.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
39447
305.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
49533
384.1 IPS |
|
|
Style Transfer (F32)
|
100% |
40333
53.1 IPS |
|
|
Style Transfer (F16)
|
100% |
140612
185.0 IPS |
|
|
Style Transfer (I8)
|
100% |
147552
194.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9990
356.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
33158
1.18 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
30398
1.09 KIPS |
|
|
Text Classification (F32)
|
100% |
2039
2.93 KIPS |
|
|
Text Classification (F16)
|
100% |
3399
4.88 KIPS |
|
|
Text Classification (I8)
|
96% |
3329
4.78 KIPS |
|
|
Machine Translation (F32)
|
100% |
853
15.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1402
25.8 IPS |
|
|
Machine Translation (I8)
|
99% |
843
15.5 IPS |
