MacBook Pro (16-inch, 2023)
Geekbench AI Score
4214
Single Precision Score
6821
Half Precision Score
5335
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| User | richh- |
| Upload Date | February 07 2025 12:21 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 15.3 (Build 24D60) |
| 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% |
1416
263.4 IPS |
|
|
Image Classification (HP)
|
100% |
2315
430.6 IPS |
|
|
Image Classification (Q)
|
96% |
1668
311.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1728
28.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2629
42.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
3000
48.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
13010
15.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
25404
29.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
19349
22.7 IPS |
|
|
Object Detection (SP)
|
100% |
1708
135.5 IPS |
|
|
Object Detection (HP)
|
97% |
2739
218.0 IPS |
|
|
Object Detection (Q)
|
94% |
2014
160.5 IPS |
|
|
Face Detection (SP)
|
100% |
3766
44.8 IPS |
|
|
Face Detection (HP)
|
100% |
5941
70.6 IPS |
|
|
Face Detection (Q)
|
100% |
3408
40.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6336
48.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
12086
93.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
8162
63.8 IPS |
|
|
Style Transfer (SP)
|
100% |
24812
31.9 IPS |
|
|
Style Transfer (HP)
|
100% |
39168
50.4 IPS |
|
|
Style Transfer (Q)
|
96% |
29666
38.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5126
189.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7148
264.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4500
166.2 IPS |
|
|
Text Classification (SP)
|
100% |
2312
3.09 KIPS |
|
|
Text Classification (HP)
|
100% |
4023
5.37 KIPS |
|
|
Text Classification (Q)
|
93% |
4018
5.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
4634
79.8 IPS |
|
|
Machine Translation (HP)
|
98% |
6373
110.1 IPS |
|
|
Machine Translation (Q)
|
98% |
6422
111.0 IPS |
