MacBook Pro (16-inch, 2023)
Geekbench AI Score
4177
Single Precision Score
6733
Half Precision Score
5350
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| Upload Date | November 18 2024 01:22 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B83) |
| 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 | 3.67 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1384
257.5 IPS |
|
|
Image Classification (HP)
|
100% |
2288
425.6 IPS |
|
|
Image Classification (Q)
|
96% |
1691
315.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1700
27.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2637
42.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
3050
49.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
12988
15.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
25164
29.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
19490
22.8 IPS |
|
|
Object Detection (SP)
|
100% |
1697
134.6 IPS |
|
|
Object Detection (HP)
|
97% |
2716
216.2 IPS |
|
|
Object Detection (Q)
|
94% |
2024
161.3 IPS |
|
|
Face Detection (SP)
|
100% |
3662
43.5 IPS |
|
|
Face Detection (HP)
|
100% |
5975
71.0 IPS |
|
|
Face Detection (Q)
|
100% |
3551
42.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6383
49.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
12060
93.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
8210
64.2 IPS |
|
|
Style Transfer (SP)
|
100% |
24958
32.1 IPS |
|
|
Style Transfer (HP)
|
100% |
38248
49.2 IPS |
|
|
Style Transfer (Q)
|
96% |
30120
38.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5113
188.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6861
253.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4417
163.1 IPS |
|
|
Text Classification (SP)
|
100% |
2279
3.04 KIPS |
|
|
Text Classification (HP)
|
100% |
3953
5.28 KIPS |
|
|
Text Classification (Q)
|
93% |
3929
5.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
4588
79.0 IPS |
|
|
Machine Translation (HP)
|
98% |
6216
107.4 IPS |
|
|
Machine Translation (Q)
|
98% |
6201
107.2 IPS |
