| User | iPhil |
| Upload Date | January 27 2025 01:53 PM |
| Views | 19 |
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple M3 Max |
| System Information | |
|---|---|
| Operating System | macOS 15.3 (Build 24D60) |
| Model | MacBook Pro (16-inch, Nov 2023) |
| Model ID | Mac15,9 |
| Motherboard | Mac15,9 |
| CPU Information | |
|---|---|
| Name | Apple M3 Max |
| Topology | 1 Processor, 16 Cores |
| Identifier | Apple M3 Max |
| Base Frequency | 3.86 GHz |
| Cluster 1 | 12 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
7824
1.45 KIPS |
|
|
Image Classification (HP)
|
100% |
8472
1.58 KIPS |
|
|
Image Classification (Q)
|
97% |
7147
1.33 KIPS |
|
|
Image Segmentation (SP)
|
100% |
16706
270.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
17627
285.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
18059
292.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
91552
106.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
95467
111.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
89335
104.7 IPS |
|
|
Object Detection (SP)
|
100% |
5373
426.2 IPS |
|
|
Object Detection (HP)
|
100% |
5580
442.6 IPS |
|
|
Object Detection (Q)
|
91% |
6906
551.9 IPS |
|
|
Face Detection (SP)
|
100% |
26517
315.1 IPS |
|
|
Face Detection (HP)
|
100% |
33621
399.5 IPS |
|
|
Face Detection (Q)
|
100% |
26721
317.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
37727
290.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
39751
306.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
34081
266.4 IPS |
|
|
Style Transfer (SP)
|
100% |
187434
240.9 IPS |
|
|
Style Transfer (HP)
|
100% |
204718
263.2 IPS |
|
|
Style Transfer (Q)
|
96% |
190108
245.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
25000
923.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
26403
974.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
21868
807.5 IPS |
|
|
Text Classification (SP)
|
100% |
2784
3.72 KIPS |
|
|
Text Classification (HP)
|
100% |
4893
6.53 KIPS |
|
|
Text Classification (Q)
|
93% |
4925
6.61 KIPS |
|
|
Machine Translation (SP)
|
100% |
1349
23.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1561
26.9 IPS |
|
|
Machine Translation (Q)
|
98% |
1482
25.6 IPS |