MacBook Pro (14-inch, 2023)
Geekbench AI Score
4173
Single Precision Score
6736
Half Precision Score
5272
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, 12 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.48 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1399
260.2 IPS |
|
|
Image Classification (HP)
|
100% |
2268
421.9 IPS |
|
|
Image Classification (Q)
|
96% |
1662
310.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1695
27.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2582
41.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
2958
47.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
12992
15.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
25824
30.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
18893
22.1 IPS |
|
|
Object Detection (SP)
|
100% |
1702
135.0 IPS |
|
|
Object Detection (HP)
|
97% |
2736
217.8 IPS |
|
|
Object Detection (Q)
|
94% |
2022
161.2 IPS |
|
|
Face Detection (SP)
|
100% |
3646
43.3 IPS |
|
|
Face Detection (HP)
|
100% |
5786
68.8 IPS |
|
|
Face Detection (Q)
|
100% |
3350
39.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6332
48.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
12089
93.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
8240
64.4 IPS |
|
|
Style Transfer (SP)
|
100% |
24691
31.7 IPS |
|
|
Style Transfer (HP)
|
100% |
38654
49.7 IPS |
|
|
Style Transfer (Q)
|
96% |
29098
37.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5106
188.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6896
254.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4442
164.0 IPS |
|
|
Text Classification (SP)
|
100% |
2284
3.05 KIPS |
|
|
Text Classification (HP)
|
100% |
4008
5.35 KIPS |
|
|
Text Classification (Q)
|
93% |
3964
5.32 KIPS |
|
|
Machine Translation (SP)
|
100% |
4596
79.2 IPS |
|
|
Machine Translation (HP)
|
98% |
6223
107.5 IPS |
|
|
Machine Translation (Q)
|
98% |
6254
108.1 IPS |
