Mac mini (2023)
Geekbench AI Score
3071
Single Precision Score
23292
Half Precision Score
25468
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| Upload Date | December 24 2024 09:44 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 15.0.1 (Build 24A348) |
| 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 | 3.42 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1267
235.6 IPS |
|
|
Image Classification (HP)
|
100% |
14660
2.73 KIPS |
|
|
Image Classification (Q)
|
96% |
15479
2.89 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1399
22.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
9818
159.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
10991
178.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6509
7.59 IPS |
|
|
Pose Estimation (HP)
|
100% |
105116
122.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
96962
113.6 IPS |
|
|
Object Detection (SP)
|
100% |
1313
104.1 IPS |
|
|
Object Detection (HP)
|
99% |
15262
1.21 KIPS |
|
|
Object Detection (Q)
|
91% |
17876
1.43 KIPS |
|
|
Face Detection (SP)
|
100% |
1953
23.2 IPS |
|
|
Face Detection (HP)
|
100% |
31885
378.9 IPS |
|
|
Face Detection (Q)
|
100% |
41595
494.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
5286
40.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
86329
665.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
108865
850.7 IPS |
|
|
Style Transfer (SP)
|
100% |
17018
21.9 IPS |
|
|
Style Transfer (HP)
|
100% |
201536
259.1 IPS |
|
|
Style Transfer (Q)
|
96% |
194154
250.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3885
143.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
41857
1.55 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
52327
1.93 KIPS |
|
|
Text Classification (SP)
|
100% |
2214
2.95 KIPS |
|
|
Text Classification (HP)
|
100% |
3722
4.97 KIPS |
|
|
Text Classification (Q)
|
93% |
3702
4.97 KIPS |
|
|
Machine Translation (SP)
|
100% |
3267
56.3 IPS |
|
|
Machine Translation (HP)
|
100% |
2356
40.6 IPS |
|
|
Machine Translation (Q)
|
98% |
2286
39.5 IPS |
