MacBook Pro (16-inch, 2023)
Geekbench AI Score
2035
Single Precision Score
3175
Half Precision Score
2776
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| User | carson1125 |
| Upload Date | May 27 2025 01:13 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 15.5 (Build 24F74) |
| Model | MacBook Pro (16-inch, 2023) |
| Model ID | Mac14,6 |
| Motherboard | Mac14,6 |
| CPU Information | |
|---|---|
| Name | Apple M2 Max |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Max |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1272
236.6 IPS |
|
|
Image Classification (HP)
|
100% |
2047
380.7 IPS |
|
|
Image Classification (Q)
|
96% |
951
177.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
725
11.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1074
17.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
1736
28.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
5883
6.86 IPS |
|
|
Pose Estimation (HP)
|
100% |
10118
11.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
8929
10.5 IPS |
|
|
Object Detection (SP)
|
100% |
790
62.7 IPS |
|
|
Object Detection (HP)
|
97% |
1474
117.4 IPS |
|
|
Object Detection (Q)
|
94% |
852
67.9 IPS |
|
|
Face Detection (SP)
|
100% |
1872
22.2 IPS |
|
|
Face Detection (HP)
|
100% |
3483
41.4 IPS |
|
|
Face Detection (Q)
|
100% |
1675
19.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
3926
30.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
5830
45.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
4881
38.2 IPS |
|
|
Style Transfer (SP)
|
100% |
13817
17.8 IPS |
|
|
Style Transfer (HP)
|
100% |
18354
23.6 IPS |
|
|
Style Transfer (Q)
|
96% |
17162
22.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1794
66.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2213
81.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1971
72.8 IPS |
|
|
Text Classification (SP)
|
100% |
920
1.23 KIPS |
|
|
Text Classification (HP)
|
100% |
1438
1.92 KIPS |
|
|
Text Classification (Q)
|
93% |
2540
3.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
1703
29.3 IPS |
|
|
Machine Translation (HP)
|
98% |
2681
46.3 IPS |
|
|
Machine Translation (Q)
|
98% |
3081
53.2 IPS |
