Mac mini (2023)
Geekbench AI Score
6784
Single Precision Score
7644
Half Precision Score
6792
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| User | urix |
| Upload Date | February 24 2025 07:12 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 15.3.1 (Build 24D70) |
| Model | Mac mini (2023) |
| Model ID | Mac14,3 |
| Motherboard | Mac14,3 |
| CPU Information | |
|---|---|
| Name | Apple M2 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M2 |
| Base Frequency | 3.48 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3727
693.0 IPS |
|
|
Image Classification (HP)
|
100% |
3651
678.9 IPS |
|
|
Image Classification (Q)
|
97% |
3048
568.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
4029
65.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
5005
81.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
5098
82.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
24591
28.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
26325
30.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
24469
28.7 IPS |
|
|
Object Detection (SP)
|
100% |
3502
277.8 IPS |
|
|
Object Detection (HP)
|
100% |
3737
296.4 IPS |
|
|
Object Detection (Q)
|
91% |
3083
246.4 IPS |
|
|
Face Detection (SP)
|
100% |
10385
123.4 IPS |
|
|
Face Detection (HP)
|
100% |
11992
142.5 IPS |
|
|
Face Detection (Q)
|
100% |
8391
99.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
16686
128.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
17910
138.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
15029
117.5 IPS |
|
|
Style Transfer (SP)
|
100% |
42939
55.2 IPS |
|
|
Style Transfer (HP)
|
100% |
48660
62.6 IPS |
|
|
Style Transfer (Q)
|
96% |
45487
58.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9791
361.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
10476
386.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
8350
308.3 IPS |
|
|
Text Classification (SP)
|
100% |
2244
3.00 KIPS |
|
|
Text Classification (HP)
|
100% |
3750
5.01 KIPS |
|
|
Text Classification (Q)
|
93% |
3735
5.01 KIPS |
|
|
Machine Translation (SP)
|
100% |
977
16.8 IPS |
|
|
Machine Translation (HP)
|
100% |
923
15.9 IPS |
|
|
Machine Translation (Q)
|
98% |
997
17.2 IPS |
