MacBook Pro (16-inch, 2023)
Geekbench AI Score
3171
Single Precision Score
4737
Half Precision Score
3939
Quantized Score
Geekbench AI 1.0.0 for macOS AArch64
Result Information
| Upload Date | August 22 2024 03:19 PM |
| Views | 17 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| 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 | 3.66 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 96.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1457
271.0 IPS |
|
|
Image Classification (HP)
|
100% |
1785
332.0 IPS |
|
|
Image Classification (Q)
|
99% |
1819
339.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1308
21.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1310
21.2 IPS |
|
|
Image Segmentation (Q)
|
100% |
1309
21.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6124
7.15 IPS |
|
|
Pose Estimation (HP)
|
100% |
14595
17.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
12374
14.5 IPS |
|
|
Object Detection (SP)
|
100% |
1562
123.9 IPS |
|
|
Object Detection (HP)
|
97% |
2185
173.9 IPS |
|
|
Object Detection (Q)
|
94% |
1689
134.6 IPS |
|
|
Face Detection (SP)
|
100% |
2971
35.3 IPS |
|
|
Face Detection (HP)
|
100% |
4403
52.3 IPS |
|
|
Face Detection (Q)
|
100% |
2852
33.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5406
41.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
8485
65.6 IPS |
|
|
Depth Estimation (Q)
|
96% |
4239
32.8 IPS |
|
|
Style Transfer (SP)
|
100% |
16630
21.4 IPS |
|
|
Style Transfer (HP)
|
100% |
26504
34.1 IPS |
|
|
Style Transfer (Q)
|
100% |
26353
33.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3783
139.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4814
177.8 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
3525
130.6 IPS |
|
|
Text Classification (SP)
|
100% |
2274
3.04 KIPS |
|
|
Text Classification (HP)
|
100% |
3588
4.79 KIPS |
|
|
Text Classification (Q)
|
93% |
3591
4.82 KIPS |
|
|
Machine Translation (SP)
|
100% |
2455
42.3 IPS |
|
|
Machine Translation (HP)
|
98% |
4468
77.2 IPS |
|
|
Machine Translation (Q)
|
98% |
4481
77.4 IPS |
