MacBook Pro (14-inch, 2023)
Geekbench AI Score
4171
Single Precision Score
6853
Half Precision Score
5348
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| Upload Date | February 17 2025 06:26 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.3 (Build 24D60) |
| 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 | 3.48 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1410
262.3 IPS |
|
|
Image Classification (HP)
|
100% |
2286
425.1 IPS |
|
|
Image Classification (Q)
|
96% |
1665
310.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1741
28.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2697
43.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
2972
48.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
12731
14.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
25767
30.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
19127
22.4 IPS |
|
|
Object Detection (SP)
|
100% |
1712
135.8 IPS |
|
|
Object Detection (HP)
|
97% |
2734
217.6 IPS |
|
|
Object Detection (Q)
|
94% |
2036
162.3 IPS |
|
|
Face Detection (SP)
|
100% |
3726
44.3 IPS |
|
|
Face Detection (HP)
|
100% |
5937
70.5 IPS |
|
|
Face Detection (Q)
|
100% |
3484
41.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
6385
49.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
12239
94.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
8283
64.8 IPS |
|
|
Style Transfer (SP)
|
100% |
24880
32.0 IPS |
|
|
Style Transfer (HP)
|
100% |
39001
50.1 IPS |
|
|
Style Transfer (Q)
|
96% |
29517
38.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5188
191.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7286
269.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4487
165.7 IPS |
|
|
Text Classification (SP)
|
100% |
2365
3.16 KIPS |
|
|
Text Classification (HP)
|
100% |
4064
5.42 KIPS |
|
|
Text Classification (Q)
|
93% |
4108
5.51 KIPS |
|
|
Machine Translation (SP)
|
100% |
4106
70.7 IPS |
|
|
Machine Translation (HP)
|
98% |
6269
108.3 IPS |
|
|
Machine Translation (Q)
|
98% |
6336
109.5 IPS |
