Mac mini (2023)
Geekbench AI Score
3438
Single Precision Score
28191
Half Precision Score
31386
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| Upload Date | November 09 2024 03:30 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B83) |
| 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% |
1388
258.1 IPS |
|
|
Image Classification (HP)
|
100% |
14775
2.75 KIPS |
|
|
Image Classification (Q)
|
96% |
15635
2.92 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1506
24.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
19222
311.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
23594
382.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6811
7.95 IPS |
|
|
Pose Estimation (HP)
|
100% |
106538
124.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
106262
124.5 IPS |
|
|
Object Detection (SP)
|
100% |
1532
121.5 IPS |
|
|
Object Detection (HP)
|
99% |
15850
1.26 KIPS |
|
|
Object Detection (Q)
|
91% |
17979
1.44 KIPS |
|
|
Face Detection (SP)
|
100% |
3039
36.1 IPS |
|
|
Face Detection (HP)
|
100% |
33535
398.5 IPS |
|
|
Face Detection (Q)
|
100% |
42746
507.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5652
43.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
87815
676.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
111102
868.2 IPS |
|
|
Style Transfer (SP)
|
100% |
18613
23.9 IPS |
|
|
Style Transfer (HP)
|
100% |
202604
260.4 IPS |
|
|
Style Transfer (Q)
|
96% |
194470
251.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4132
152.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
43093
1.59 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
51332
1.90 KIPS |
|
|
Text Classification (SP)
|
100% |
2254
3.01 KIPS |
|
|
Text Classification (HP)
|
100% |
3794
5.06 KIPS |
|
|
Text Classification (Q)
|
93% |
3797
5.10 KIPS |
|
|
Machine Translation (SP)
|
100% |
3560
61.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6777
116.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7314
126.4 IPS |
