Mac mini (2023)
Geekbench AI Score
3151
Single Precision Score
4727
Half Precision Score
4104
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| User | Meddog |
| Upload Date | March 27 2025 03:34 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 14.7.4 (Build 23H420) |
| Model | Mac mini (2023) |
| Model ID | Mac14,12 |
| Motherboard | Mac14,12 |
| 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% |
1482
275.5 IPS |
|
|
Image Classification (HP)
|
100% |
1832
340.7 IPS |
|
|
Image Classification (Q)
|
96% |
1446
270.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1291
20.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
1280
20.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
1842
29.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
6274
7.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
14875
17.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
12811
15.0 IPS |
|
|
Object Detection (SP)
|
100% |
1614
128.0 IPS |
|
|
Object Detection (HP)
|
97% |
2232
177.7 IPS |
|
|
Object Detection (Q)
|
94% |
1726
137.6 IPS |
|
|
Face Detection (SP)
|
100% |
2984
35.5 IPS |
|
|
Face Detection (HP)
|
100% |
4363
51.8 IPS |
|
|
Face Detection (Q)
|
100% |
2871
34.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
5526
42.6 IPS |
|
|
Depth Estimation (HP)
|
97% |
8594
66.4 IPS |
|
|
Depth Estimation (Q)
|
86% |
6525
50.9 IPS |
|
|
Style Transfer (SP)
|
100% |
16981
21.8 IPS |
|
|
Style Transfer (HP)
|
100% |
26783
34.4 IPS |
|
|
Style Transfer (Q)
|
96% |
22437
29.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3820
141.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4744
175.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3652
134.8 IPS |
|
|
Text Classification (SP)
|
100% |
2278
3.04 KIPS |
|
|
Text Classification (HP)
|
100% |
3345
4.47 KIPS |
|
|
Text Classification (Q)
|
93% |
3369
4.52 KIPS |
|
|
Machine Translation (SP)
|
100% |
2050
35.3 IPS |
|
|
Machine Translation (HP)
|
98% |
4496
77.7 IPS |
|
|
Machine Translation (Q)
|
98% |
4456
77.0 IPS |
