Mac mini (2023)
Geekbench AI Score
3311
Single Precision Score
26079
Half Precision Score
28487
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| Upload Date | January 12 2025 01:00 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 15.2 (Build 24C101) |
| 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 | 3.47 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1318
245.1 IPS |
|
|
Image Classification (HP)
|
100% |
14120
2.63 KIPS |
|
|
Image Classification (Q)
|
96% |
14305
2.67 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1445
23.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
19025
308.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
23610
382.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
6178
7.21 IPS |
|
|
Pose Estimation (HP)
|
100% |
106094
123.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
105733
123.9 IPS |
|
|
Object Detection (SP)
|
100% |
1469
116.5 IPS |
|
|
Object Detection (HP)
|
99% |
15587
1.24 KIPS |
|
|
Object Detection (Q)
|
91% |
17345
1.39 KIPS |
|
|
Face Detection (SP)
|
100% |
3008
35.7 IPS |
|
|
Face Detection (HP)
|
100% |
32551
386.8 IPS |
|
|
Face Detection (Q)
|
100% |
36583
434.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
5427
41.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
86547
666.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
107736
841.9 IPS |
|
|
Style Transfer (SP)
|
100% |
17993
23.1 IPS |
|
|
Style Transfer (HP)
|
100% |
202221
260.0 IPS |
|
|
Style Transfer (Q)
|
96% |
194374
250.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4038
149.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
38813
1.43 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
49006
1.81 KIPS |
|
|
Text Classification (SP)
|
100% |
2259
3.01 KIPS |
|
|
Text Classification (HP)
|
100% |
3791
5.06 KIPS |
|
|
Text Classification (Q)
|
93% |
3749
5.03 KIPS |
|
|
Machine Translation (SP)
|
100% |
3421
58.9 IPS |
|
|
Machine Translation (HP)
|
100% |
3909
67.3 IPS |
|
|
Machine Translation (Q)
|
98% |
4038
69.8 IPS |
