MacBook Pro (14-inch, 2023)
Geekbench AI Score
4154
Single Precision Score
6709
Half Precision Score
5282
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| Upload Date | January 07 2025 10:13 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 15.2 (Build 24C101) |
| 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 | 3.45 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1386
257.8 IPS |
|
|
Image Classification (HP)
|
100% |
2264
421.0 IPS |
|
|
Image Classification (Q)
|
96% |
1658
309.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1682
27.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2534
41.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
2932
47.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
12776
14.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
24603
28.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
19353
22.7 IPS |
|
|
Object Detection (SP)
|
100% |
1687
133.8 IPS |
|
|
Object Detection (HP)
|
97% |
2731
217.4 IPS |
|
|
Object Detection (Q)
|
94% |
2019
160.9 IPS |
|
|
Face Detection (SP)
|
100% |
3635
43.2 IPS |
|
|
Face Detection (HP)
|
100% |
5759
68.4 IPS |
|
|
Face Detection (Q)
|
100% |
3295
39.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
6280
48.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
12277
94.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
8212
64.2 IPS |
|
|
Style Transfer (SP)
|
100% |
24558
31.6 IPS |
|
|
Style Transfer (HP)
|
100% |
38224
49.1 IPS |
|
|
Style Transfer (Q)
|
96% |
29341
37.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5089
187.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7035
259.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4473
165.2 IPS |
|
|
Text Classification (SP)
|
100% |
2333
3.11 KIPS |
|
|
Text Classification (HP)
|
100% |
4051
5.41 KIPS |
|
|
Text Classification (Q)
|
93% |
4005
5.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
4581
78.9 IPS |
|
|
Machine Translation (HP)
|
98% |
6226
107.6 IPS |
|
|
Machine Translation (Q)
|
98% |
6261
108.2 IPS |
