MacBook Pro (14-inch, 2023)
Geekbench AI Score
4146
Single Precision Score
27658
Half Precision Score
30886
Quantized Score
Geekbench AI 1.4.0 for macOS AArch64
Result Information
| User | natrat |
| Upload Date | July 20 2025 02:43 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.5 (Build 24F74) |
| Model | MacBook Pro (14-inch, 2023) |
| Model ID | Mac14,9 |
| Motherboard | Mac14,9 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.49 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1403
261.0 IPS |
|
|
Image Classification (HP)
|
100% |
15257
2.84 KIPS |
|
|
Image Classification (Q)
|
96% |
17933
3.35 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1670
27.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
20128
326.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
24955
404.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
12790
14.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
106290
124.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
104257
122.2 IPS |
|
|
Object Detection (SP)
|
100% |
1689
134.0 IPS |
|
|
Object Detection (HP)
|
99% |
15765
1.25 KIPS |
|
|
Object Detection (Q)
|
91% |
17627
1.41 KIPS |
|
|
Face Detection (SP)
|
100% |
3566
42.4 IPS |
|
|
Face Detection (HP)
|
100% |
35885
426.4 IPS |
|
|
Face Detection (Q)
|
100% |
46448
551.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6166
47.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
89159
686.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
112624
880.1 IPS |
|
|
Style Transfer (SP)
|
100% |
24793
31.9 IPS |
|
|
Style Transfer (HP)
|
100% |
205637
264.3 IPS |
|
|
Style Transfer (Q)
|
96% |
192974
249.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5119
189.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
43576
1.61 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
51626
1.91 KIPS |
|
|
Text Classification (SP)
|
100% |
2419
3.23 KIPS |
|
|
Text Classification (HP)
|
100% |
4138
5.52 KIPS |
|
|
Text Classification (Q)
|
93% |
4115
5.52 KIPS |
|
|
Machine Translation (SP)
|
100% |
4397
75.7 IPS |
|
|
Machine Translation (HP)
|
100% |
4291
73.9 IPS |
|
|
Machine Translation (Q)
|
98% |
4480
77.4 IPS |
