MacBook Pro (14-inch, 2023)
Geekbench AI Score
4023
Single Precision Score
6692
Half Precision Score
5278
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| Upload Date | July 02 2025 09:28 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.5 (Build 24F74) |
| Model | MacBook Pro (14-inch, 2023) |
| Model ID | Mac14,9 |
| Motherboard | Mac14,9 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.42 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1399
260.2 IPS |
|
|
Image Classification (HP)
|
100% |
2219
412.7 IPS |
|
|
Image Classification (Q)
|
96% |
1623
303.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1632
26.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2481
40.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
2803
45.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
12642
14.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
25420
29.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
19462
22.8 IPS |
|
|
Object Detection (SP)
|
100% |
1643
130.3 IPS |
|
|
Object Detection (HP)
|
97% |
2626
209.1 IPS |
|
|
Object Detection (Q)
|
94% |
1886
150.3 IPS |
|
|
Face Detection (SP)
|
100% |
3439
40.9 IPS |
|
|
Face Detection (HP)
|
100% |
5616
66.7 IPS |
|
|
Face Detection (Q)
|
100% |
3242
38.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6020
46.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
11153
86.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
7705
60.2 IPS |
|
|
Style Transfer (SP)
|
100% |
25107
32.3 IPS |
|
|
Style Transfer (HP)
|
100% |
39318
50.5 IPS |
|
|
Style Transfer (Q)
|
96% |
30668
39.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4499
166.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6691
247.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4452
164.4 IPS |
|
|
Text Classification (SP)
|
100% |
2317
3.09 KIPS |
|
|
Text Classification (HP)
|
100% |
4134
5.52 KIPS |
|
|
Text Classification (Q)
|
93% |
4127
5.54 KIPS |
|
|
Machine Translation (SP)
|
100% |
4324
74.5 IPS |
|
|
Machine Translation (HP)
|
98% |
7198
124.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7143
123.4 IPS |
