MacBook Pro (14-inch, 2023)
Geekbench AI Score
4147
Single Precision Score
6730
Half Precision Score
5301
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| Upload Date | December 23 2024 07:53 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.1.1 (Build 24B91) |
| Model | MacBook Pro (14-inch, 2023) |
| Model ID | Mac14,9 |
| Motherboard | Mac14,9 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.47 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1406
261.4 IPS |
|
|
Image Classification (HP)
|
100% |
2261
420.5 IPS |
|
|
Image Classification (Q)
|
96% |
1654
309.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1686
27.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2532
41.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
2932
47.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
12692
14.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
24885
29.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
18917
22.2 IPS |
|
|
Object Detection (SP)
|
100% |
1700
134.9 IPS |
|
|
Object Detection (HP)
|
97% |
2734
217.6 IPS |
|
|
Object Detection (Q)
|
94% |
2002
159.6 IPS |
|
|
Face Detection (SP)
|
100% |
3646
43.3 IPS |
|
|
Face Detection (HP)
|
100% |
5787
68.8 IPS |
|
|
Face Detection (Q)
|
100% |
3514
41.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6408
49.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
12331
95.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
8221
64.3 IPS |
|
|
Style Transfer (SP)
|
100% |
25009
32.2 IPS |
|
|
Style Transfer (HP)
|
100% |
39511
50.8 IPS |
|
|
Style Transfer (Q)
|
96% |
29793
38.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5098
188.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6942
256.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4435
163.8 IPS |
|
|
Text Classification (SP)
|
100% |
2285
3.05 KIPS |
|
|
Text Classification (HP)
|
100% |
3966
5.29 KIPS |
|
|
Text Classification (Q)
|
93% |
3995
5.36 KIPS |
|
|
Machine Translation (SP)
|
100% |
4325
74.5 IPS |
|
|
Machine Translation (HP)
|
98% |
6313
109.1 IPS |
|
|
Machine Translation (Q)
|
98% |
6268
108.3 IPS |
