Mac mini (2023)
Geekbench AI Score
6662
Single Precision Score
7520
Half Precision Score
6690
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| User | mthocker |
| Upload Date | April 10 2025 10:30 PM |
| Views | 21 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 15.3.2 (Build 24D81) |
| 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 | 3.49 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3631
675.3 IPS |
|
|
Image Classification (HP)
|
100% |
3583
666.3 IPS |
|
|
Image Classification (Q)
|
97% |
2954
551.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
3876
62.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
4952
80.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
5065
82.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
24219
28.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
25876
30.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
24285
28.5 IPS |
|
|
Object Detection (SP)
|
100% |
3335
264.6 IPS |
|
|
Object Detection (HP)
|
100% |
3708
294.2 IPS |
|
|
Object Detection (Q)
|
91% |
3059
244.4 IPS |
|
|
Face Detection (SP)
|
100% |
9705
115.3 IPS |
|
|
Face Detection (HP)
|
100% |
11064
131.5 IPS |
|
|
Face Detection (Q)
|
100% |
8365
99.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
16311
125.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
17259
133.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
14836
116.0 IPS |
|
|
Style Transfer (SP)
|
100% |
42450
54.6 IPS |
|
|
Style Transfer (HP)
|
100% |
48150
61.9 IPS |
|
|
Style Transfer (Q)
|
96% |
45390
58.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9750
360.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
10003
369.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
7918
292.4 IPS |
|
|
Text Classification (SP)
|
100% |
2277
3.04 KIPS |
|
|
Text Classification (HP)
|
100% |
3807
5.08 KIPS |
|
|
Text Classification (Q)
|
93% |
3831
5.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
1016
17.5 IPS |
|
|
Machine Translation (HP)
|
100% |
971
16.7 IPS |
|
|
Machine Translation (Q)
|
98% |
946
16.3 IPS |
