MacBook Pro (16-inch, 2023)
Geekbench AI Score
4046
Single Precision Score
6517
Half Precision Score
5237
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| Upload Date | June 14 2025 08:48 AM |
| Views | 3 |
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 | 3.61 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1375
255.6 IPS |
|
|
Image Classification (HP)
|
100% |
2225
413.8 IPS |
|
|
Image Classification (Q)
|
96% |
1665
310.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1622
26.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2509
40.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
2853
46.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
12586
14.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
24301
28.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
19164
22.5 IPS |
|
|
Object Detection (SP)
|
100% |
1634
129.6 IPS |
|
|
Object Detection (HP)
|
97% |
2622
208.7 IPS |
|
|
Object Detection (Q)
|
94% |
1902
151.6 IPS |
|
|
Face Detection (SP)
|
100% |
3460
41.1 IPS |
|
|
Face Detection (HP)
|
100% |
5506
65.4 IPS |
|
|
Face Detection (Q)
|
100% |
3191
37.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6109
47.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
10912
84.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
7710
60.3 IPS |
|
|
Style Transfer (SP)
|
100% |
24325
31.3 IPS |
|
|
Style Transfer (HP)
|
100% |
37767
48.5 IPS |
|
|
Style Transfer (Q)
|
96% |
29917
38.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4970
183.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6466
238.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4472
165.1 IPS |
|
|
Text Classification (SP)
|
100% |
2374
3.17 KIPS |
|
|
Text Classification (HP)
|
100% |
4038
5.39 KIPS |
|
|
Text Classification (Q)
|
93% |
4042
5.43 KIPS |
|
|
Machine Translation (SP)
|
100% |
4231
72.9 IPS |
|
|
Machine Translation (HP)
|
98% |
6564
113.4 IPS |
|
|
Machine Translation (Q)
|
98% |
6745
116.6 IPS |
