MacBook Pro (14-inch, 2023)
Geekbench AI Score
4151
Single Precision Score
6681
Half Precision Score
5229
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| Upload Date | March 29 2025 04:48 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.3.2 (Build 24D81) |
| 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 | 3.47 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1409
262.1 IPS |
|
|
Image Classification (HP)
|
100% |
2231
415.0 IPS |
|
|
Image Classification (Q)
|
96% |
1642
306.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1692
27.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2538
41.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
2913
47.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
12758
14.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
24534
28.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
18825
22.1 IPS |
|
|
Object Detection (SP)
|
100% |
1675
132.9 IPS |
|
|
Object Detection (HP)
|
97% |
2675
212.9 IPS |
|
|
Object Detection (Q)
|
94% |
1984
158.2 IPS |
|
|
Face Detection (SP)
|
100% |
3596
42.7 IPS |
|
|
Face Detection (HP)
|
100% |
5907
70.2 IPS |
|
|
Face Detection (Q)
|
100% |
3362
39.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6314
48.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
12288
95.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
8089
63.2 IPS |
|
|
Style Transfer (SP)
|
100% |
24768
31.8 IPS |
|
|
Style Transfer (HP)
|
100% |
38435
49.4 IPS |
|
|
Style Transfer (Q)
|
96% |
28800
37.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5016
185.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6894
254.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4389
162.1 IPS |
|
|
Text Classification (SP)
|
100% |
2339
3.12 KIPS |
|
|
Text Classification (HP)
|
100% |
4000
5.34 KIPS |
|
|
Text Classification (Q)
|
93% |
3977
5.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
4523
77.9 IPS |
|
|
Machine Translation (HP)
|
98% |
6198
107.1 IPS |
|
|
Machine Translation (Q)
|
98% |
6264
108.2 IPS |
