MacBook Pro (14-inch, 2023)
Geekbench AI Score
4133
Single Precision Score
27563
Half Precision Score
30646
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| User | justadri |
| Upload Date | December 13 2024 10:56 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| 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% |
1388
258.2 IPS |
|
|
Image Classification (HP)
|
100% |
14497
2.70 KIPS |
|
|
Image Classification (Q)
|
96% |
16862
3.15 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1692
27.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
19460
315.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
24643
399.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
12725
14.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
107026
124.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
104166
122.1 IPS |
|
|
Object Detection (SP)
|
100% |
1680
133.3 IPS |
|
|
Object Detection (HP)
|
99% |
15566
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
17005
1.36 KIPS |
|
|
Face Detection (SP)
|
100% |
3590
42.7 IPS |
|
|
Face Detection (HP)
|
100% |
35041
416.4 IPS |
|
|
Face Detection (Q)
|
100% |
44337
526.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6197
47.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
88712
683.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
111302
869.8 IPS |
|
|
Style Transfer (SP)
|
100% |
25037
32.2 IPS |
|
|
Style Transfer (HP)
|
100% |
206716
265.7 IPS |
|
|
Style Transfer (Q)
|
96% |
194019
250.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5153
190.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
42617
1.57 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
50603
1.87 KIPS |
|
|
Text Classification (SP)
|
100% |
2262
3.02 KIPS |
|
|
Text Classification (HP)
|
100% |
3983
5.32 KIPS |
|
|
Text Classification (Q)
|
93% |
3959
5.31 KIPS |
|
|
Machine Translation (SP)
|
100% |
4469
77.0 IPS |
|
|
Machine Translation (HP)
|
100% |
4938
85.1 IPS |
|
|
Machine Translation (Q)
|
98% |
5176
89.5 IPS |
