MacBook Pro (14-inch, Nov 2023)
Geekbench ML Score
9559
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 17 2024 06:25 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6 (Build 23G80) |
| Model | MacBook Pro (14-inch, Nov 2023) |
| Model ID | Mac15,10 |
| Motherboard | Mac15,10 |
| CPU Information | |
|---|---|
| Name | Apple M3 Max |
| Topology | 1 Processor, 14 Cores |
| Identifier | Apple M3 Max |
| Base Frequency | 4.05 GHz |
| Cluster 1 | 10 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 | 36.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6307
1.18 KIPS |
|
|
Image Classification (F16)
|
100% |
6568
1.23 KIPS |
|
|
Image Classification (I8)
|
99% |
6000
1.12 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2910
48.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
3002
50.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
2918
48.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
61894
75.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
65519
79.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
63126
76.4 IPS |
|
|
Object Detection (F32)
|
100% |
4546
339.4 IPS |
|
|
Object Detection (F16)
|
100% |
5125
382.6 IPS |
|
|
Object Detection (I8)
|
97% |
4072
304.0 IPS |
|
|
Face Detection (F32)
|
100% |
20890
248.4 IPS |
|
|
Face Detection (F16)
|
98% |
24262
288.5 IPS |
|
|
Face Detection (I8)
|
97% |
22346
265.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
30509
236.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
32646
253.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
31392
243.4 IPS |
|
|
Style Transfer (F32)
|
100% |
128971
169.6 IPS |
|
|
Style Transfer (F16)
|
100% |
137561
180.9 IPS |
|
|
Style Transfer (I8)
|
100% |
135434
178.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9380
335.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11211
400.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
11249
401.7 IPS |
|
|
Text Classification (F32)
|
100% |
1390
2.00 KIPS |
|
|
Text Classification (F16)
|
100% |
870
1.25 KIPS |
|
|
Text Classification (I8)
|
96% |
909
1.31 KIPS |
|
|
Machine Translation (F32)
|
100% |
1151
21.2 IPS |
|
|
Machine Translation (F16)
|
99% |
1187
21.8 IPS |
|
|
Machine Translation (I8)
|
99% |
1113
20.5 IPS |
