| User | mweinbach |
| Upload Date | December 08 2023 04:50 PM |
| Views | 10 |
| System Information | |
|---|---|
| Operating System | macOS 14.2 (Build 23C64) |
| 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 | 4.05 GHz |
| Cluster 1 | 12 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 128.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
5609
1.05 KIPS |
|
|
Image Classification (F16)
|
100% |
6825
1.28 KIPS |
|
|
Image Classification (I8)
|
99% |
6057
1.13 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2274
38.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
2335
39.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
2366
39.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
83863
101.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
86879
105.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
82647
100.1 IPS |
|
|
Object Detection (F32)
|
100% |
3605
269.1 IPS |
|
|
Object Detection (F16)
|
100% |
5022
374.9 IPS |
|
|
Object Detection (I8)
|
97% |
4203
313.8 IPS |
|
|
Face Detection (F32)
|
100% |
23575
280.3 IPS |
|
|
Face Detection (F16)
|
97% |
23551
280.0 IPS |
|
|
Face Detection (I8)
|
96% |
22260
264.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
37245
288.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
37267
289.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
36121
280.1 IPS |
|
|
Style Transfer (F32)
|
100% |
171922
226.1 IPS |
|
|
Style Transfer (F16)
|
100% |
179977
236.7 IPS |
|
|
Style Transfer (I8)
|
100% |
176548
232.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
12969
463.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
14276
509.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
10427
372.4 IPS |
|
|
Text Classification (F32)
|
100% |
964
1.38 KIPS |
|
|
Text Classification (F16)
|
100% |
869
1.25 KIPS |
|
|
Text Classification (I8)
|
96% |
870
1.25 KIPS |
|
|
Machine Translation (F32)
|
100% |
1001
18.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1013
18.6 IPS |
|
|
Machine Translation (I8)
|
99% |
935
17.2 IPS |