MacBook Pro (14-inch, 2023)
Geekbench AI Score
4150
Single Precision Score
21139
Half Precision Score
23327
Quantized Score
Geekbench AI 1.0.0 for macOS AArch64
Result Information
| User | Bishop_Swift |
| Upload Date | August 16 2024 09:15 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B5024e) |
| Model | MacBook Pro (14-inch, 2023) |
| Model ID | Mac14,9 |
| Motherboard | Mac14,9 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.48 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1386
257.8 IPS |
|
|
Image Classification (HP)
|
100% |
13506
2.51 KIPS |
|
|
Image Classification (Q)
|
99% |
16062
3.00 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1666
27.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
9210
149.3 IPS |
|
|
Image Segmentation (Q)
|
100% |
9141
148.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
13021
15.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
102886
120.1 IPS |
|
|
Pose Estimation (Q)
|
94% |
97673
114.6 IPS |
|
|
Object Detection (SP)
|
100% |
1695
134.4 IPS |
|
|
Object Detection (HP)
|
99% |
13814
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
16487
1.32 KIPS |
|
|
Face Detection (SP)
|
100% |
3630
43.1 IPS |
|
|
Face Detection (HP)
|
100% |
23693
281.5 IPS |
|
|
Face Detection (Q)
|
100% |
37004
439.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6336
48.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
73734
568.1 IPS |
|
|
Depth Estimation (Q)
|
97% |
82226
635.8 IPS |
|
|
Style Transfer (SP)
|
100% |
24853
31.9 IPS |
|
|
Style Transfer (HP)
|
100% |
157021
201.9 IPS |
|
|
Style Transfer (Q)
|
100% |
157632
202.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5107
188.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
41552
1.53 KIPS |
|
|
Image Super-Resolution (Q)
|
98% |
47878
1.77 KIPS |
|
|
Text Classification (SP)
|
100% |
2240
2.99 KIPS |
|
|
Text Classification (HP)
|
100% |
3832
5.11 KIPS |
|
|
Text Classification (Q)
|
93% |
3823
5.13 KIPS |
|
|
Machine Translation (SP)
|
100% |
4549
78.4 IPS |
|
|
Machine Translation (HP)
|
100% |
2308
39.7 IPS |
|
|
Machine Translation (Q)
|
98% |
2299
39.7 IPS |
