MacBook Pro (14-inch, 2023)
Geekbench AI Score
3911
Single Precision Score
6616
Half Precision Score
5291
Quantized Score
Geekbench AI 1.5.0 for macOS AArch64
Result Information
| Upload Date | December 09 2025 12:41 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 26.1 (Build 25B78) |
| 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 | 3.46 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1307
243.1 IPS |
|
|
Image Classification (HP)
|
100% |
2260
420.2 IPS |
|
|
Image Classification (Q)
|
96% |
1660
310.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1646
26.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2474
40.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
2867
46.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
11695
13.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
25936
30.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
19591
23.0 IPS |
|
|
Object Detection (SP)
|
100% |
1459
115.7 IPS |
|
|
Object Detection (HP)
|
97% |
2526
201.1 IPS |
|
|
Object Detection (Q)
|
94% |
1853
147.7 IPS |
|
|
Face Detection (SP)
|
100% |
3412
40.5 IPS |
|
|
Face Detection (HP)
|
100% |
5907
70.2 IPS |
|
|
Face Detection (Q)
|
100% |
3276
38.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5767
44.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
11001
85.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
7839
61.3 IPS |
|
|
Style Transfer (SP)
|
100% |
24117
31.0 IPS |
|
|
Style Transfer (HP)
|
100% |
38599
49.6 IPS |
|
|
Style Transfer (Q)
|
96% |
31235
40.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4729
174.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6331
233.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4294
158.6 IPS |
|
|
Text Classification (SP)
|
100% |
2440
3.26 KIPS |
|
|
Text Classification (HP)
|
99% |
3989
5.32 KIPS |
|
|
Text Classification (Q)
|
93% |
4051
5.44 KIPS |
|
|
Machine Translation (SP)
|
100% |
4171
71.8 IPS |
|
|
Machine Translation (HP)
|
98% |
6935
119.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7142
123.4 IPS |
