MacBook Pro (14-inch, 2023)
Geekbench AI Score
4164
Single Precision Score
6752
Half Precision Score
5284
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| Upload Date | November 19 2024 02:13 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 (14-inch, 2023) |
| Model ID | Mac14,5 |
| Motherboard | Mac14,5 |
| CPU Information | |
|---|---|
| Name | Apple M2 Max |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Max |
| Base Frequency | 3.47 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 96.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1371
255.0 IPS |
|
|
Image Classification (HP)
|
100% |
2139
397.7 IPS |
|
|
Image Classification (Q)
|
96% |
1628
304.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1689
27.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2550
41.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
2895
46.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
12838
15.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
25557
29.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
19136
22.4 IPS |
|
|
Object Detection (SP)
|
100% |
1686
133.8 IPS |
|
|
Object Detection (HP)
|
97% |
2728
217.2 IPS |
|
|
Object Detection (Q)
|
94% |
1967
156.8 IPS |
|
|
Face Detection (SP)
|
100% |
3559
42.3 IPS |
|
|
Face Detection (HP)
|
100% |
6017
71.5 IPS |
|
|
Face Detection (Q)
|
100% |
3406
40.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6240
48.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
12125
93.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
8141
63.6 IPS |
|
|
Style Transfer (SP)
|
100% |
25291
32.5 IPS |
|
|
Style Transfer (HP)
|
100% |
38985
50.1 IPS |
|
|
Style Transfer (Q)
|
96% |
30164
38.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5086
187.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7066
260.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4432
163.7 IPS |
|
|
Text Classification (SP)
|
100% |
2329
3.11 KIPS |
|
|
Text Classification (HP)
|
100% |
4029
5.38 KIPS |
|
|
Text Classification (Q)
|
93% |
4007
5.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
4701
81.0 IPS |
|
|
Machine Translation (HP)
|
98% |
6399
110.6 IPS |
|
|
Machine Translation (Q)
|
98% |
6444
111.4 IPS |
