MacBook Pro (14-inch, Nov 2023)
Geekbench ML Score
9523
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 17 2024 04:17 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| 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% |
6639
1.24 KIPS |
|
|
Image Classification (F16)
|
100% |
6929
1.30 KIPS |
|
|
Image Classification (I8)
|
99% |
6441
1.21 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2783
46.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
2943
49.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
2885
48.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
62465
75.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
66132
80.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
63624
77.0 IPS |
|
|
Object Detection (F32)
|
100% |
4663
348.1 IPS |
|
|
Object Detection (F16)
|
100% |
5189
387.4 IPS |
|
|
Object Detection (I8)
|
97% |
4505
336.3 IPS |
|
|
Face Detection (F32)
|
100% |
21378
254.2 IPS |
|
|
Face Detection (F16)
|
98% |
24803
294.9 IPS |
|
|
Face Detection (I8)
|
97% |
21551
256.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
32367
251.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
34259
265.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
31509
244.4 IPS |
|
|
Style Transfer (F32)
|
100% |
130097
171.1 IPS |
|
|
Style Transfer (F16)
|
100% |
143240
188.4 IPS |
|
|
Style Transfer (I8)
|
100% |
137131
180.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
11970
427.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
14397
514.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
10453
373.3 IPS |
|
|
Text Classification (F32)
|
100% |
920
1.32 KIPS |
|
|
Text Classification (F16)
|
100% |
588
845.1 IPS |
|
|
Text Classification (I8)
|
96% |
675
970.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1197
22.0 IPS |
|
|
Machine Translation (F16)
|
99% |
1198
22.0 IPS |
|
|
Machine Translation (I8)
|
99% |
1196
22.0 IPS |
