MacBook Pro (13-inch, 2022)
Geekbench AI Score
3432
Single Precision Score
6004
Half Precision Score
4877
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| User | EdwinValdezEXD |
| Upload Date | May 25 2025 04:51 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 15.5 (Build 24F74) |
| 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 | 3.47 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1389
258.4 IPS |
|
|
Image Classification (HP)
|
100% |
2530
470.5 IPS |
|
|
Image Classification (Q)
|
96% |
1765
329.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1480
24.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2424
39.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
2769
44.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
6799
7.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
15116
17.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
12907
15.1 IPS |
|
|
Object Detection (SP)
|
100% |
1527
121.2 IPS |
|
|
Object Detection (HP)
|
97% |
2790
222.2 IPS |
|
|
Object Detection (Q)
|
94% |
2031
161.9 IPS |
|
|
Face Detection (SP)
|
100% |
3058
36.3 IPS |
|
|
Face Detection (HP)
|
100% |
5855
69.6 IPS |
|
|
Face Detection (Q)
|
100% |
3447
41.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
5522
42.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
10960
84.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
7701
60.2 IPS |
|
|
Style Transfer (SP)
|
100% |
18577
23.9 IPS |
|
|
Style Transfer (HP)
|
100% |
29027
37.3 IPS |
|
|
Style Transfer (Q)
|
96% |
23936
30.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3968
146.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5005
184.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3701
136.7 IPS |
|
|
Text Classification (SP)
|
100% |
2303
3.07 KIPS |
|
|
Text Classification (HP)
|
100% |
3950
5.27 KIPS |
|
|
Text Classification (Q)
|
93% |
3923
5.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
3715
64.0 IPS |
|
|
Machine Translation (HP)
|
98% |
6397
110.5 IPS |
|
|
Machine Translation (Q)
|
98% |
6444
111.4 IPS |
