MacBook Pro (16-inch, 2023)
Geekbench AI Score
4119
Single Precision Score
6662
Half Precision Score
5300
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| Upload Date | June 14 2025 01:38 PM |
| Views | 1 |
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 | 3.66 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1390
258.5 IPS |
|
|
Image Classification (HP)
|
100% |
2263
420.9 IPS |
|
|
Image Classification (Q)
|
96% |
1596
298.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1650
26.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2519
40.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
2942
47.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
12888
15.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
25818
30.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
19888
23.3 IPS |
|
|
Object Detection (SP)
|
100% |
1692
134.2 IPS |
|
|
Object Detection (HP)
|
97% |
2648
210.8 IPS |
|
|
Object Detection (Q)
|
94% |
1992
158.8 IPS |
|
|
Face Detection (SP)
|
100% |
3493
41.5 IPS |
|
|
Face Detection (HP)
|
100% |
5672
67.4 IPS |
|
|
Face Detection (Q)
|
100% |
3346
39.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6074
46.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
11358
87.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
7759
60.7 IPS |
|
|
Style Transfer (SP)
|
100% |
25136
32.3 IPS |
|
|
Style Transfer (HP)
|
100% |
38449
49.4 IPS |
|
|
Style Transfer (Q)
|
96% |
29625
38.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5040
186.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6492
239.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4509
166.5 IPS |
|
|
Text Classification (SP)
|
100% |
2358
3.15 KIPS |
|
|
Text Classification (HP)
|
100% |
4069
5.43 KIPS |
|
|
Text Classification (Q)
|
93% |
4060
5.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
4441
76.5 IPS |
|
|
Machine Translation (HP)
|
98% |
6763
116.9 IPS |
|
|
Machine Translation (Q)
|
98% |
6680
115.4 IPS |
