MacBook Pro (13-inch, 2022)
Geekbench AI Score
3446
Single Precision Score
5973
Half Precision Score
4851
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| User | Aaronage |
| Upload Date | November 14 2024 10:28 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B83) |
| 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 | 3.48 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 24.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1392
258.9 IPS |
|
|
Image Classification (HP)
|
100% |
2532
470.9 IPS |
|
|
Image Classification (Q)
|
96% |
1769
330.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1531
24.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2488
40.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
2896
46.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
6870
8.02 IPS |
|
|
Pose Estimation (HP)
|
100% |
14874
17.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
12834
15.0 IPS |
|
|
Object Detection (SP)
|
100% |
1554
123.3 IPS |
|
|
Object Detection (HP)
|
97% |
2892
230.2 IPS |
|
|
Object Detection (Q)
|
94% |
2088
166.5 IPS |
|
|
Face Detection (SP)
|
100% |
3061
36.4 IPS |
|
|
Face Detection (HP)
|
100% |
6148
73.0 IPS |
|
|
Face Detection (Q)
|
100% |
3536
42.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
5680
43.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
11637
90.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
8064
63.0 IPS |
|
|
Style Transfer (SP)
|
100% |
18707
24.0 IPS |
|
|
Style Transfer (HP)
|
100% |
28510
36.6 IPS |
|
|
Style Transfer (Q)
|
96% |
23800
30.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4044
149.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4812
177.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3564
131.6 IPS |
|
|
Text Classification (SP)
|
100% |
2229
2.97 KIPS |
|
|
Text Classification (HP)
|
100% |
3774
5.04 KIPS |
|
|
Text Classification (Q)
|
93% |
3749
5.03 KIPS |
|
|
Machine Translation (SP)
|
100% |
3546
61.1 IPS |
|
|
Machine Translation (HP)
|
98% |
5766
99.6 IPS |
|
|
Machine Translation (Q)
|
98% |
5805
100.3 IPS |
